U.S. patent application number 13/282313 was filed with the patent office on 2012-02-09 for system and method for an electronic product advisor.
This patent application is currently assigned to CBS Interactive, Inc.. Invention is credited to Patrick Cashman Andrus, Scott Bedard, Greg Kasavin.
Application Number | 20120035981 13/282313 |
Document ID | / |
Family ID | 37525171 |
Filed Date | 2012-02-09 |
United States Patent
Application |
20120035981 |
Kind Code |
A1 |
Bedard; Scott ; et
al. |
February 9, 2012 |
System and Method for an Electronic Product Advisor
Abstract
A system and method operates on a client device and acquires a
suspect list of user products based on information derived from the
client device. The system normalizes the list, and the user
confirms the accuracy of the product list. The user product list is
sent to a server where the user product list is compared to other
lists using collaborative filtering techniques. The collaborative
filtering techniques determine products of interest for the use and
the level of interest of the user. The system computes a similarity
measure based upon the number of similar products that match the
user's product list and rankings provided by the user and others.
Demographic and behavioral data may also be used in performing the
comparison and the similarity measure. The system acquires
editorial rankings of products from other users and provides a
ranked list of recommended products based upon the editorial
rankings.
Inventors: |
Bedard; Scott; (San
Francisco, CA) ; Kasavin; Greg; (Mill Valley, CA)
; Andrus; Patrick Cashman; (San Francisco, CA) |
Assignee: |
CBS Interactive, Inc.
San Francisco
CA
|
Family ID: |
37525171 |
Appl. No.: |
13/282313 |
Filed: |
October 26, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11415416 |
May 2, 2006 |
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13282313 |
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60676280 |
May 2, 2005 |
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Current U.S.
Class: |
705/7.29 |
Current CPC
Class: |
G06F 16/9535 20190101;
G06Q 30/0202 20130101; G06Q 30/0631 20130101; G06Q 30/0201
20130101; G06Q 30/0217 20130101; G06Q 30/02 20130101; G06Q 30/0251
20130101; G06Q 30/0255 20130101; G06Q 30/0601 20130101; G06Q
30/0204 20130101; G06Q 30/0623 20130101; G06Q 30/0241 20130101 |
Class at
Publication: |
705/7.29 |
International
Class: |
G06Q 30/02 20120101
G06Q030/02 |
Claims
1. A computer implemented method for establishing and maintaining
an online community of users of products, the method comprising:
via an Internet-compatible communications interface, receiving data
regarding a plurality of users, and receiving data regarding at
least one user-owned product, the data regarding at least one
user-owned product including a price of the product; associating at
least one user-owned product having received price data with at
least one product user; estimating the value of at least one
associated product, at least in part as a function of received
price data; and via the Internet-compatible communications
interface, providing functionality allowing each profiled user to
search and retrieve an estimated used value of a product, including
the cumulative used value of a subset of products associated with
the user and having estimated prices.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of prior U.S. Utility
patent application Ser. No. 11/415,416, filed May 2, 2006 of the
same title (Attorney Docket No. 20109.0033.NPUS00), which claims
the benefit of U.S. Provisional Patent Application No. 60/676,280,
filed May 2 2005, entitled "System and Method for Online Gaming
Community" (Attorney Docket No. 20109.0033.PZUS00), the disclosure
of each being hereby incorporated herein by reference in its
entirety.
FIELD OF THE INVENTION
[0002] The present invention relates to collaborative filtering
systems that produce personal recommendations by determining the
similarity between a user and others. More particularly, it relates
to systems and methods for providing product recommendations based
upon user preferences and the preferences of users with similar
characteristics. The recommended products include retail goods and
services as well as electronic products such as games, computer
programs, music files, and the like.
BACKGROUND OF THE INVENTION
[0003] In recent years, networks and interconnectivity of
individuals, groups, and organizations has dramatically increased.
The Internet connects the world by joining billions of connected
users that represent various entities, information, and resources.
These connected users form enormous banks of resources, resulting
in a world wide web of users. The users store and access documents
or web pages, identified by uniform resource locators (URL), that
can be accessed by other connected nodes on the network. This vast
data store allows previously obscure or unknown information to be
disseminated throughout the world. The users perform a wide range
of activities such as accessing information sources including news,
weather, sports, and financial sites. Other users buy and sell
products and services in electronic commerce systems.
[0004] One of the primary applications of the Web has been
shopping, that is, the purchase of goods and services. Virtually
every major commercial "brick and mortar" merchant has established
a Web site for the showcase and sale of their products. Further,
many manufacturers sell products directly over the Web. Finally, a
plethora of on-line merchants, not previously existing in the brick
and mortar world, have come into existence. As a result, virtually
every product is available for purchase over the Web from a
plurality of merchants. This situation has increased the efficiency
of markets by permitting shoppers to readily compare products and
terms of sale from plural merchants without the need to physically
travel to the merchant locations.
[0005] With this increase in efficiency of markets has come an
increased burden on the consumer of these products. To determine
the best quality, lowest price product now requires a consumer to
sift through volumes and volumes of potential providers. To reduce
the number of irrelevant product providers and to increase the
quality of a consumer's search, information regarding potential
providers may be filtered to deliver the most relevant providers to
the user.
[0006] Information filtering is performed in a number of ways. For
example, a customary consumer telephone directory of businesses,
such as the Yellow Pages, filters product providers by geographic
calling area. Further, Internet Service Providers and Internet
portals also classify information by categorizing web pages by
topics such as news, sports, entertainment, and the like. However,
these broad subject areas are not always sufficient to locate
information of interest to a consumer.
[0007] More sophisticated techniques for filtering products of
interest to consumers may be employed by identifying information
about the user. These methods may monitor and record a consumer's
purchase behavior or other patterns of behavior. Information may be
collected by means of surveys, questionnaires, opinion polls, and
the like. These conventional techniques may be extrapolated to the
networked world by means of inferential tracking programs, cookies,
and other techniques designed to obtain consumer information with
minimal consumer effort and minimal expenditure of resources.
[0008] Information may be transferred and stored on a consumer's
computer by a web server to monitor and record information related
to a user's web-related activities. The user's web-related
information may include information about product browsing, product
selections, and purchases made by the user at web pages hosted by a
web server. The information stored by the inferential tracking
programs is typically accessed and used by the web server when the
particular server or web page is again accessed by the user
computer. Cookies may be used by web servers to identify users, to
instruct the server to send a customized version of the requested
web page to the client computer, to submit account information for
the user, and so forth. Explicit and implicit user information
collection techniques are used by a large number of web-based
providers of goods and services including eBay.R.TM..,
Amazon..TM.., and others. In some instances, user information
gathered by the servers is used to create personalized profiles for
the users. The customized profiles are then used to summarize the
user's activities at one or more web pages associated with the
server.
[0009] Current shopping advisory systems focus on enhanced shopping
carts to provide suggested additional products a user may purchase,
while others have developed advisory systems to provide product
recommendations based in part on a vendor payment to sort the
vendor's product to the top of the list.
[0010] Conventional shopping advisory systems focus on a point of
sale event and only take into account a user's imminent product
purchase and possibly prior purchases from the specific merchant.
These prior systems do not cover all related products a user
acquired from a variety of sources.
[0011] Further, these conventional systems do not utilize user
profile information based on collected demographics, user ratings,
and behavioral data. Without this profile data, conventional
systems do not provide personalized product information.
[0012] Finally, conventional systems typically do not incorporate
unbiased professional editorial product reviews and ratings or
end-user product reviews and ratings. Because they lack this
editorial data, the typical advisory systems do not factor
editorial rankings into the purchase advice.
[0013] Filtering methods based upon the content of the user's
activities may be used to reach information, goods, and services
for the user based upon correlations between the user's activities
and the items. The filtering methods and customized profiles may
then be used to recommend or suggest additional information, goods,
and services in which the user may be interested.
[0014] Filtering methods serve to organize the array of
information, goods, and services to assist the user by presenting
materials that the user is more likely to be interested in, or by
directing the user to materials that the user may find useful.
Filtering attempts to sift through the vast stores of information
while detecting and uncovering less conspicuous information that
may be of interest to the user. The filtering methods attempt to
locate items of meaningful information that would otherwise be
obscured by the volume of irrelevant information vying for the
attention of the user.
[0015] Information filtering may be directed to content-based
filtering where keywords or key articles are examined and semantic
and syntactic information are used to determine a user's interests.
Additionally, expert systems may be utilized to "learn" a user's
behavior patterns. For example, expert systems or intelligent
software agents may note a user's actions in response to a variety
of stimuli and then respond in the same manner when similar stimuli
present in the future.
[0016] As expert systems grow, or as intelligent software agents
expand to cover additional users or groups, the range and accuracy
of the responses may be refined to increase the efficiency of the
system. Collaboration among users or groups of like users results
in increased accuracy with regard to predicting future user
responses based upon past responses. Evaluating feedback of other
similar users is effective in determining how a similar user will
respond to similar stimuli. Users that agreed in the past will
likely agree in the future. These collaborative filtering methods
may use weighted averaging techniques for user feedback that
extracts ratings for articles such as information, goods, services,
and the like, to predict whether an article is relevant to a
particular user. With weighted averages, however, the character of
the content is ignored or otherwise obscured during the averaging
process because personal preferences, credibility, and other
factors are lost.
[0017] What is needed is a system and a method of combining user
profile information with collaborative and editorial data to
provide users with credible information regarding information,
goods, and services.
SUMMARY OF THE INVENTION
[0018] The present invention relates to a system and method of
combining user profile information with collaborative and editorial
data to provide users with credible information regarding
information, goods, and services. The system and method may
incorporate collaborative filtering and profiling measures to
provide recommended products and to provide a forum in which users
with similar characteristics and interests may communicate
further.
[0019] A preferred embodiment of the present invention
programmatically acquires a suspect list of items that a user
already owns or desires to own, which the user then confirms and
adds relevant ratings, demographic, and behavioral data. This data
is then compared to a database of product lists and ratings from
similar users. A similarity measure is computed for each product
list based on the number of similar products contained on the list
that match the consumer's list, rankings, behavioral, and
demographic data. A ranked list of recommended products that the
consumer does not own is then computed based on the similarity
measure and the editorial ratings of the product. The invention
then causes the ranked list to be displayed to the consumer. The
ranked list may then be modified based on additional variables.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] The accompanying drawings illustrate an embodiment of the
invention and depict the above-mentioned and other features of this
invention and the manner of attaining them. In the drawings:
[0021] FIG. 1 illustrates an exemplary computer network in
accordance with an embodiment of the present invention.
[0022] FIG. 2 illustrates an exemplary comparison module in
accordance with the present invention.
[0023] FIGS. 3A-3D show a flow chart illustrating methods in
accordance with the present invention for presenting a ranked
recommended product list to a user.
[0024] FIGS. 4A and 4B illustrate an example of a community page
template and a screen shot of a community page, respectively.
[0025] FIGS. 5A-5C illustrate examples of the Community Review
pages served by a system and method in accordance with the present
invention.
[0026] FIGS. 6A-6D illustrate examples of the Community User
ratings pages served by a system and method in accordance with the
present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0027] The following detailed description of the invention refers
to the accompanying drawings and to certain preferred embodiments,
but the detailed description of the invention does not limit the
invention. The scope of the invention is defined by the appended
claims and equivalents as it will be apparent to those of skill in
the art that various features, variations, and modifications can be
included or excluded based upon the requirements of a particular
use.
[0028] The present invention extends the functionality of current
collaborative filtering techniques to provide an advisory method
combining user profiling based on demographic and behavioral data
with collaborative and user and editorial rating data to provide a
ranked list of recommended products. The present invention provides
a ranked list of recommended "products" but is intended to cover
additional items such as games, music, computer programs, and other
goods and services that may exist in a less-tangible form than a
concrete product. One of ordinary skill in the art would understand
that the term "product" should also be extended to encompass these
other goods and services as well. For brevity, the term "product"
as used in conjunction with the present invention should be
understood to cover these other items and other similar goods and
services as well.
[0029] The system and method of the present invention has many
advantages over prior systems because the product advisor results
are tailored to a particular user based on demographic and
behavioral data with collaborative, user, and editorial rating data
to reduce irrelevant results. The present invention may be
customized for individual users to return topically relevant
products and lists to significantly reduce the overall locating
times and processing resources required while providing improved
relevancy, consistency, and reliability in delivering pertinent
results.
[0030] FIG. 1 illustrates an exemplary computer system in which
concepts and methods consistent with the present invention may be
performed.
[0031] As shown in FIG. 1, system 100 comprises a number of users
101a, 101b, 101c, 101d from which a suspect list of user products
may be acquired. Users 101a, 101b, 101c, 101d may be individuals,
groups, clients, servers, and the like. Users 101a, 101b, 101c,
101d may access an advisor server performing the method of the
present invention, such as advisor server 150 comprising an
acquisition module 152, comparison module 154, computation module
156, and display module 158 with which to access a database 160 of
products. For clarity and brevity, four users 101a, 101b, 101c,
101d are shown, but it should be understood that any number of
users may use the system 100 with which to access recommended
products in a database 160. Database 160 may also be a network of
databases as well, connected to advisor server 150 or accessible by
advisor server 150. Likewise, it should also be understood that any
number of advisor servers may be used by the system. Multiple
advisor servers may be segregated by geographic location, by the
type or number of recommended products that they offer, or by any
number of criteria commonly used to configure server farms, web
farms, or otherwise distribute computing resources and workloads
between multiple computers and multiple modules.
[0032] For clarity and brevity, a single advisor server 150
comprising acquisition module 152, comparison module 154,
computation module 156, display module 158, and database 160 is
shown. It should also be understood that users 101a, 101b, 101c,
101d and advisor server 150 may be substituted for one another.
That is, any user 101a, 101b, 101c, 101d may access recommended
products housed and stored by another user. Advisor server 150 is
illustrated as component modules 152, 154, 156, 158, 160 merely to
show a preferred embodiment and a preferred configuration. The
recommended product lists can be in a distributed environment, such
as servers on the World Wide Web.
[0033] Users 101a, 101b, 101c, 101d may access advisor server 150
through any computer network 198 including the Internet,
telecommunications networks in any suitable form, local area
networks, wide area networks, wireless communications networks,
cellular communications networks, G3 communications networks,
Public Switched Telephone Networks (PSTNs), Packet Data Networks
(PDNs), intranets, or any combination of these networks or any
group of two or more computers linked together with the ability to
communicate with each other.
[0034] As illustrated in FIG. 1, computer network 198 may be the
Internet where users 101a, 101b, 101c, 101d are nodes on the
network as is advisor server 150. Users 101a, 101b, 101c, 101d and
advisor server 150 may be any suitable device capable of providing
a document to another device. For example these devices may be any
suitable servers, workstations, PCs, laptop computers, PDAs,
Internet appliances, handheld devices, cellular telephones,
wireless devices, other devices, and the like, capable of
performing the processes of the exemplary embodiments of FIGS. 1-6.
The devices and subsystems of the exemplary embodiments of FIGS.
1-6 can communicate with each other using any suitable protocol and
can be implemented using one or more programmed computer systems or
devices. In general, these devices may be any type of computing
platform connected to a network and interacting with application
programs.
[0035] Likewise, while component modules 152, 154, 156, 158, 160
are illustrated in FIG. 1 as being in advisor server 150, these
component modules 152, 154, 156, 158, 160 may also be separate
computing devices on computer network 198.
[0036] The computer component modules 152, 154, 156, 158, 160 are
discussed below in greater detail and with reference to the process
flow diagrams FIGS. 3A, 3B, 3C, 3D.
[0037] Acquire
[0038] In step 302, acquisition module 152 acquires a suspect list
of user products such as a list of consumer electronics devices
maintained in user's computer 101a, a list of mp3 files stored in a
group's computer 101d, a list of computer games stored on an
organization's server 101b, or a list of relevant information
located on consumer's computer 101c. Similarly, the system and
method of the present invention may acquire a suspect list of user
products from any electronic device of the consumer, such as a
portable digital assistant (PDA), a handset, a smart phone, a
cellular phone, and the like. The suspect list of user products may
be acquired in a number of ways. For example, the acquisition
module 152 may initiate a system scan of the user's computer 101a,
101b, 101c, 101d to examine a user's files or programs. This system
scan may be performed with or without the user's knowledge or
permission, depending upon the circumstances of the scan and the
anticipated type of products expected to reside on the users'
computers 101a, 101b, 101c, 101d. For example, when attempting to
access a suspect list of computer game program files, acquisition
module 152 may initiate a system scan of user computer 101a after
requesting permission of the operator of user computer 101a.
[0039] Conversely, acquisition module 152 may commence a system
scan of an organization's computer 101b at a predetermined interval
to examine computer files, game programs, and the like. This type
of system scan may have a user's tacit knowledge as a condition of
his or her participation in the advisor server environment. In any
event, the acquisition module 152 initiates a system scan to
acquire a suspect list of user products.
[0040] Likewise, acquisition module 152 may also collect
information from a user 101a, 101b, 101c, 101d as the user searches
a web site or other network location for products. The browsed
products may then be added to the suspect list. For example, a user
101a, 101b, 101c, 101d may be shopping for a particular computer
game and store a title or description of a suspect game to a user's
collection. Acquisition module 152 may collect information
regarding the products from the user's collection, shopping carts,
or other interim holding and listing mechanism.
[0041] Also, acquisition module 152 may track web site usage or
network usage and add suspect products to a list. For example, a
user may view a particular product web page. Acquisition module 152
may then acquire product information from the visited web pages and
add suspect products to the user's suspect product list based upon
the type of web page. Additionally, acquisition module 152 may
acquire suspect product information by analyzing a web site or
network location and importing the information from a web page
itself. For example, a web page, a collection of web pages, or a
document located on a visited network location may be parsed to
generate a list of commonly-occurring terms, product information,
or suspect products, and the suspect products may be added to the
suspect product list. The forgoing examples are illustrations only,
and other suitable techniques may be used to acquire a suspect list
of user products and to update an existing suspect list of user
products within the present invention.
[0042] Normalize
[0043] Regardless of the manner in which acquisition module 152
acquires a suspect list of user products, after the list is
acquired in step 302, in step 304 it is normalized or matched to a
standardized product list that is maintained on the Advisor Server
150.
[0044] The normalization process is optional and may be performed
before, during, or after the suspect list of user products is
updated. The normalization process serves to provide a measure of
standardization when different users refer to the same product.
This standardization promotes searching and reporting efficiencies
within the system by reducing the number of database queries
required.
[0045] Confirm
[0046] After the suspect list of user products is normalized to a
product list on the product advisor server, in step 306 the system
prompts the user to confirm the status of the products listed. That
is, the user acknowledges that the normalized or standardized
naming of the suspect product is in line with the user's
understanding of the suspect product and that the normalized name
accurately describes the product.
[0047] Product List Categorization
[0048] After the user acknowledges that the normalized list of
suspect products is an accurate representation of the products, in
step 308 the user begins to separate the products that he already
owns from the products that he would like to own. If the user
already owns the product, in step 310 the user adds the product to
an Owned Products List. In step 312 the user ranks the product on
the Owned Products List. If the user does not already own the
product, but decides in step 314 that he would like to own the
item, the product is added to a Wish List in step 316. In step 318,
the user ranks the product on the Wish List. If, in step 314, the
user determines that they do not wish to own the suspect product,
the product listing is discarded and the process stops in step
399.
[0049] Send Lists
[0050] In step 320, the user can send their Owned Product List or
Wish List to the Advisor Server, to another user, or to a
Group.
[0051] Sent to Advisor Server
[0052] If the user sends their list to the Advisor Server, in step
322 the invention acquires product lists from other users from a
database of product lists. These other acquired lists will serve as
a basis of comparison with which the user's product list may be
evaluated.
[0053] The invention checks to see if the user is registered in
step 324, and if the user is registered, additional demographic
data from a database of demographic data is also acquired in step
326. Additionally, behavioral data from a behavioral data database
is acquired in step 328. These demographic and behavioral data may
be stored in database 160 or any database otherwise accessible by
advisor server 150. For registered users, these additional
demographic and behavioral data supplement the product lists
acquired in step 322. The additional demographic and behavioral
data form the basis for additional comparisons with the user
product lists and product lists acquired from other users. If a
user is not registered, optional registration means may be provided
to enable the user to subscribe to the system.
[0054] Once the product list from other users and any demographic
data and behavioral data is acquired, the user confirms the product
list is accurate in step 330. The user may edit the product list by
adding, deleting, or modifying the product list to ensure it is
accurate.
[0055] Compare Lists Using Similarity Measurement
[0056] After the user confirms that the product list is accurate,
in step 332 the comparison module 154 compares the user's owned
product list, wish list, demographic and behavioral data (if
applicable), and rankings with lists acquired from other users from
the database of product lists.
[0057] To conduct this comparison, in step 334, the computation
module 156 computes a similarity percentage for each product list
based on the number of similar products contained on the list that
match the consumer's list, rankings, behavioral, and demographic
data. A ranked list of recommended products the consumer does not
own is then computed based on the product of the similarity
percentage of a product list and the number of instances of
un-owned products and the user and editorial ratings of the
product. A ranked list of recommended products the consumer does
not own is then made available to be displayed to the user. The
user may further modify this list based on additional rankings The
following tables provide an illustration of this comparison method
and the resultant recommended product list. Other comparison
methods based on known techniques, including Boolean and frequency
weighting, clustering, and Bayesian approaches, and various
collaborative filtering techniques, may also be employed.
[0058] In Table 1, below, X represents that a particular letter
user owns a particular numbered product.
TABLE-US-00001 TABLE 1 Product 1 Product 2 Product 3 Product 4
Product 5 User A X X (consumer) User B X X User C X X User D X X X
User E X X X User F X X X
[0059] Based upon which products are owned by both User A and by a
different user, a similarity percentage is determined. The
similarity percentage is calculated by determining the number of
products that a particular letter user has in common with User A
(consumer). The similarity percentages are shown below in Table
2.
TABLE-US-00002 TABLE 2 Similarity Percentage Explanation User A N/A
User A is the basis of the comparison. (consumer) User B 0% User B
owns products 2 and 5, while User A owns products 1 and 3. User B
owns 0 of 2 products that User A owns. Therefore, the similarity
percentage is 0%. User C 0% User C owns products 2 and 5, while
User A owns products 1 and 3. User C owns 0 of 2 products that User
A owns. Therefore, the similarity percentage is 0%. User D 50% User
D owns products 3, 4, and 5, while User A owns products 1 and 3.
User D owns 1 of 2 products that User A owns. Therefore, the
similarity percentage is 50%. User E 100% User E owns products 1,
2, and 3, while User A owns products 1 and 3. User E owns 2 of 2
products that User A owns. Therefore, the similarity percentage is
100%. User F 100% User F owns products 1, 3, and 4, while User A
owns items 1 and 3. User F owns 2 of 2 products that User A owns.
Therefore, the similarity percentage is 100%.
[0060] To compute a ranked list of recommended products the
consumer does not own, the product of the similarity percentage of
a product list and the number of instances of un-owned products is
calculated. That is: (Similarity percent).times.(number of
instances of un-owned product)=ranking In the current example, the
multiplication products are calculated for products 2, 4 and 5.
They are not calculated for products 1 and 3, because User A
already owns products 1 and 3. Table 3 below illustrates this
calculation.
TABLE-US-00003 TABLE 3 Product 1 Product 2 Product 3 Product 4
Product 5 User A N/A N/A N/A N/A N/A (consumer) User B N/A (0%)
.times. 1 = 0 N/A (0%) .times. 0 = 0 (0%) .times. 1 = 0 User C N/A
(0%) .times. 1 = 0 N/A (0%) .times. 0 = 0 (0%) .times. 1 = 0 User D
N/A (50%) .times. 0 = 0 N/A (50%) .times. 1 = .5 (50%) .times. 1 =
.5 User E N/A (100%) .times. 1 = 1.00 N/A (100%) .times. 0 = 0
(100%) .times. 0 = 0 User F N/A (100%) .times. 0 = 0 N/A (100%)
.times. 1 = 1.00 (100%) .times. 0 = 0 Sum N/A 0 + 0 + 0 + 1.00 + 0
= 1.00 N/A 0 + 0 + .5 + 0 + 1.00 = 1.50 0 + 0 + .5 + 0 + 0 = .5
[0061] The sum is computed merely by adding the multiplication
product for each user for each numbered product as shown in Table
3. Once the sums are computed for each numbered product, the
un-owned products are ranked according to the largest sum. In the
example above, the recommended product list is sorted by rank
as:
[0062] Rank:
[0063] 1. Product 4 (sum is 1.50)
[0064] 2. Product 2 (sum is 1.00)
[0065] 3. Product 5 (sum is 0.5)
[0066] After the similarity measure is computed, the acquisition
module 152 acquires editorial rankings of the products in step 336.
The editorial rankings for the products serve as another mechanism
with which to sort the recommended products. The system provides
incentives to users to capture user product data, editorial
rankings, and user ratings. By encouraging users to participate in
the ranking process by providing credits and other valuable items,
a source of rating data is available. The ratings are then used to
provide recommended products such as games, music, and the like, to
other users. Similarly, with software files and downloads, a list
of the applications a user has is acquired, and the list is
compared with a database of other user lists and ratings, and a
ranked list of new software applications or downloads that the user
may like is returned. With consumer electronics and technology
products, the system compares what a user has against a database of
similar users and recommends other electronic products. Regardless
of the source of the editorial rankings and the type of product
ranked, in step 338 the ranked list of products may be sorted by
editorial rankings and presented for display by display module
158.
[0067] As further illustrated in FIG. 2, comparison module 154
receives input data including user profile information, user
product lists and ratings, and user wish lists and ratings.
Comparison module 154 works with computation module 156 to employ
collaborative filtering techniques and editorial ratings to output
a ranked recommended product list.
[0068] Upon presentation for display by the display module 158, the
user now has a ranked recommended product list. To facilitate
further action by the user, such as to purchase recommended
products or locate additional information regarding the recommended
products, in step 340 a mechanism and forum is provided in which
the user may access additional documents related to the products,
may communicate with other users, and may otherwise investigate the
listed products and other related products.
[0069] Sent to Other Users
[0070] As shown in FIG. 3C, in step 352, if the user sends their
list to other users, the acquisition module 152 acquires the other
user's lists. In step 354, comparison module 154 compares the
user's owned product list or the user's wish list with an owned
product list or wish list of another user. In step 356, the
computation module 156 computes the overlap and rankings of
products common to both the user's list and the other users to whom
the user's list was sent. Display module 158 then presents these
common products to the user. In step 358, the computation module
156 computes the separation and rankings of differing products in
both the user's list and the other users to whom the user's list
was sent. Display module 158 then makes available to the user the
ranked list of these differing products.
[0071] Upon presentation for display by the display module 158, the
user now has a ranked recommended product list. To facilitate
further action by the user, such as to purchase recommended
products or locate additional information regarding the recommended
products, in step 360 a mechanism and forum is provided in which
the user may access additional documents related to the products,
may communicate with other users, and may otherwise investigate the
listed products and other related products.
[0072] Sent to Groups
[0073] As shown in FIG. 3D, in step 380, if the user sends their
list to a Group, the acquisition module 152, comparison module 154,
computation module 156, and display module 158 carry out the method
of the invention in a similar fashion as described above with
regard to the case where a user sends the products lists to the
advisor server 150. When sending the product lists to the groups in
step 380, the acquisition module acquires product lists from
permissioned users in the Group, rather than from an entire
database of users as in the Advisor Server flow previously
discussed. In this fashion, the system acquires a smaller, but
likely more targeted set of product lists with which to compare to
the user's lists. If a user is not registered or otherwise has
permission to access the group of interest, optional registration
means may be provided to enable the user to subscribe to the
system.
[0074] As above, once the product list from group users is
acquired, the user confirms the product list is accurate in step
382. The user may edit the product list by adding, deleting, or
modifying the product list to ensure it is accurate. After the user
confirms that the product list is accurate, in step 384 the
comparison module 154 compares the user's owned product list, wish
list, and rankings with lists acquired from the group.
[0075] In step 386, the computation module 156 computes the
similarity measure as described above. Once the similarity measure
is computed, acquisition module 152 acquires editorial rankings of
products on the lists in step 388, and the computation module 156
computes the rankings of the products. Display module 158 then
makes available to the user the ranked list of products sorted by
editorial rankings in step 390.
[0076] Upon presentation for display by the display module 158, the
user now has a ranked recommended product list. To facilitate
further action by the user, such as to purchase recommended
products or locate additional information regarding the recommended
products, in step 392 a mechanism and forum is provided in which
the user may access additional documents related to the products,
may communicate with other group members, and may otherwise
investigate the listed products and other related products.
[0077] Regardless of the destination to which a user sends his
owned product list or wish list, the ranked recommended list of
products that the user receives as an output from the present
invention opens innumerable doors through which the user may
enter.
[0078] Implementations--User Preferences
[0079] For example, if the list of "products" that a user submitted
was directed to favorite computer games, a ranked recommended list
of computer games may be output and displayed to the user after
completion of the above method of the present invention. Similarly,
when a user submits a list of web sites, a ranked recommended list
of web sites is presented to the user. Drilling down further into
this example, the parsing mechanism of the present invention, as
executed by the acquisition module 152, may acquire configuration
information related to the user's favorite web sites, or
specifically the user's favorite computer game web sites. This
configuration information may be presented in steps 340, 360, and
392, respectively, depending upon the particular product lists
acquired for comparison, to allow a user to create and customize a
personal web site on a computer game home page (also referred to
herein as "GameSpot"). In this fashion, a user may configure and
personalize their favorite game site using their own preferences.
While the below examples are directed to a "product" that is a
computer game, these examples are merely illustrative of the system
and methods of the present invention, and any "product" as
discussed above, may be used.
[0080] A. User-Preference Set-Up
[0081] A user may set up a "My Games & Preferences" page that
personalizes features of a game or a game's web site for a
particular user. The "My Games & Preferences" page offers a
suite of unique, useful, and entertaining features designed to
heavily engage the user with the game system, or the game itself,
as well as provide additional game site usage and user preference
data. A user may access their personalized home page when logging
onto a game web site, such as prior to playing the game, or at any
time the user visits the web site.
[0082] For example, the web page, or the game's web page presents
the user with a login box. As soon as the user logs in, a "My Games
& Preferences" button is displayed. The user may choose to view
the preferences or skip the preferences and proceed directly to
playing the game. If the user chooses the preferences button, the
user initially views a default personalized home page configured
with colors, buttons, and style graphics based upon the user's
product lists and the ranked recommended product list of
configuration and graphics features present in the user's listed
web sites. The personalized web page can be a unique page with its
own unique URL, based on the registered user's username. If the
user elects to make his page publicly visible, it can be surfaced
from other user pages as part of their ranked recommended product
lists. Similarly, a shortcut button may be added to the user's
personalized home page to show other "GameSpotters with similar
tastes" to cull other ideas for customizing the user's home
page.
[0083] B. User Preference Features
[0084] Other features that are included in user's preferences
include user's personal space, including bio and site usage, forum
usage statistics, the user's most wanted games list, the user's
tracked games list, the user's download and data streaming
preferences, and additional buttons offering other functions such
as shortcuts to a collection of games to play, to a web storefront
where additional materials may be purchased, to a review section
offering product reviews, to a ratings page where the user may rate
games, products, and features, to a forum where users of similar
interests communicate by trading messages, to a search utility, and
to other information.
[0085] 1. User Space
[0086] A user space includes biographical and site usage
information and is based on and expanded out from a user account.
The user space allows easy access to account management and
preferences options on the home page, yet has the unique and fun
user profile features typically found in forums. Other users can
access each other's profiles, but other users cannot adjust or edit
someone else's preferences or data.
[0087] A gateway link entitled "My Games & Preferences" takes
users directly to their profile page. Also, wherever the user's
username appears on the site (e.g., reader reviews, forum posts,
etc.), the username can be hyperlinked to the user's profile
page.
[0088] The user space includes a lot of information in a limited
space. A tab structure can be employed to let the user skip over to
other areas of the page as well. Further, since user space pages
can optionally be visible to the public, the designs can look
slightly different depending on whether a user is looking at his
own page or is looking at someone else's page.
[0089] The following information is presented on the user space
page including Username (e.g., KarlB_Darkplayer), GameSpot Rank
(e.g., Level 5: Shyguy), Personal Icon, Member Since (Month/Year),
Last Online (DD-MMM-YYYY), Currently Online (Yes/No), Emblems
Earned, Real Name, Birth Date, Location (City, State/Province,
Country), Email, AOL IM, Yahoo! IM, ICQ IM, MSN IM, Xbox Live
Gamertag, and Personal Photo (or links to gallery of more photos).
This information may be required or optionally-provided depending
upon the circumstances and environment in which the user
operates.
[0090] Additionally, group and community oriented information
including Friends List, Invite a Friend (to sign up for
Basic/Complete), GS Community Center, About Me (Biographical
information), Signature (appears at the end of forum posts, reader
reviews, etc.), and Private Inbox/Send User a Private Message
designations may also be entered and displayed in the user space
page. Further, Games and Systems information may also be shown,
such as "Now Playing" list of games, My System Specs (e.g., via
system scan plug-in or manually-selected list), My Game Collection,
My Most Wanted Games, My Tracked Games, My Personal Game Store, and
a link or name for My Personal Home Page.
[0091] a. Personalized Home Page
[0092] A user's personalized home page (My Personal Home Page) can
be modeled on platform and GameSpot Live pages. Content can be
surfaced based on the user's platform and game category
preferences, and the content can be organized based on the user's
habits on the site.
[0093] For example, the content types used most frequently on the
site (news, reviews, previews, screens, movie streams, etc.) can be
prioritized on the user's personalized home page. An embedded
streaming video window can automatically appear on a user's
personalized home page, and the playlist can be catered to that
user's preferences. The GameSpot top story for the day can appear
on this page, but need not be at the top. A most popular list based
on the user's preferences can also be presented.
[0094] As the user accesses these other features of the
personalized home page, the system of the present invention tracks
the user's site usage. For example, if the user is a GameSpot user
and this week looked at Halo 2 for the Xbox and Splinter Cell for
the PC, this usage information is tracked so the system can
automatically recommend similar platform and similar game category
preferences based upon the collected data. Similarly, based on a
user's preferences, a personalized game store may be configured and
created by the acquisition module 152, comparison module 154, and
display module 158 to surface links for the user's tracked games,
top-rated games that fit their category and platform preferences,
and the like.
[0095] Additionally, data related to Forums & Contributions may
also be shown in the user space page including Most Visited Forums,
My Forums, My Recent Forum Posts, Total Number of Forum Posts, My
Reader Reviews, Total Number of Games Rated, Average Game Rating,
and My Reader Review Showcase.
[0096] Further, the user may show preferences and administrative
functions such as privacy settings (this page can be set as public
(the default) or friends-only, or anonymous), download/streaming
preferences, advertisements on/advertisements off, ice on/ice off,
notification/newsletter status (email, instant messaging, RSS),
Account management, and the like. The user preferences and account
information is accessible only to the user (not available for
public display). Other options can include transmission
capabilities such as narrowband/broadband, screen resolution,
rating system (numbers or letters), page skin/layout (choose from
various themes), local video game stores, local music stores, and
other local merchants and providers. Additionally, portable devices
(for on-the-go delivery/consumption) are also listed. Enabling
content consumption on a user's portable device, such as a mobile
phone, is shown in detail in Appendix A.
[0097] b. User Demographic Information
[0098] User demographic information is collected and may be
displayed or hidden depending upon the user's preferences. For
example, a username and personal icon may be entered. The birth
date, address, email address, and Internet Service Provider also
help characterize and profile the user. Similarly, the date that
the user began using the service, the date that the user profile
was last updated, and additional demographic information serve to
help identify and categorize the user to better provide content in
which the user will be likely to have an interest.
[0099] c. User Behavioral Information
[0100] Additional behavioral information may be collected once the
user begins accessing the site. For example, the games listed and
tracked on the user's Most Wanted List are identified and tracked.
Likewise, the user's most Visited Forums, Latest Forum Posts, Total
Number of Forum Posts, Latest Reader Reviews, Number of Games
Reviewed, Number of Games Rated, and Average Rating given are all
totaled and stored with the user's behavioral data. Similarly, the
user's Total Visits to GameSpot, Total Minutes on GameSpot, Average
Number of Pages per Session, Average Number of Visits per Week, and
Last Pages Visited on GameSpot all provide behavioral data with
which the user may be characterized to better provide content in
which the user will be likely to have an interest.
[0101] 2. User Linking
[0102] In order to increase the number of ways that users can
network with one another, the system of the present invention
properly hooks users up with other users that have similar product
tastes. For example, by compiling and analyzing the statistics
discussed above, users may view lists of other users who share
similar characteristics. A basic example is to let users view lists
of users that claim to own any given game. Another example enables
users to search for links to other users based on their collection,
their now playing list, or other list-type criteria.
[0103] The present invention enables this search by providing a
button on the profile page that says "Find Users Like Me." Clicking
this button returns a list of users and percentages, sorted by the
percentage. The percentage indicates how many of the games in the
first user's collection are owned by the other users. The cut-off
range for including users in this summary can be altered, for
example, users with at least a 50% match can be included in these
results, but that number can be adjustable in the event that 50%
returns too many or too few matches.
[0104] The system of the present invention allows users to add
games to any of their lists and get to the game-specific forum at
the GameSpace level by using an add games button. This button for
adding games also allows for a number of other features such as
List removal, where once a user has a game on any of his lists, the
user may stop tracking this game by activating the appropriate
"stop tracking this game" button or further remove the game from
the user's now playing list by activating the "remove this game
from my now playing list."
[0105] Additional features available once the user adds a game to
one of the user's lists include "XX GameSpot Users Own This Game"
where the top of the message box lists how many GameSpot users own
any given game. Clicking this link takes the user to a list of the
users that have a game in their collection. A prominent link to the
GameSpace is provided on this page as well. Similarly, a "XX
GameSpot Users Are Now Playing This Game" message may be displayed
as above, but with the Now Playing list.
[0106] An "Overall GameSpot Rank" may also be calculated based on
the lists and displayed as "Currently Ranked XXX out of YYY Games".
This feature extends the list of the top 10 most popular spaces all
the way down the site and returns a numbered rank for every single
space on the site.
[0107] a. Communities
[0108] Communities serve to unite users of similar interests and
characteristics. Communities are social network services that
enable similar users to meet, interact, and share knowledge and
items of interest. Additionally, communities offer users the
opportunity to earn rewards through active participation.
[0109] Communities allow users to create their own customizable
profile page where they can pre-set levels of privacy and access to
their personal information. From users' profile pages, user may
connect with other users through specialized "unions" or "groups,"
send private messages, create friend lists, and visit forums where
users can read posts by other users. Community pages are generated
by display module 158 upon input from the other modules 152, 154,
156, 160 in advisor server 150. An example of a community page
template is shown in FIG. 4A. This view of the community page is
also known as the Community Front Door, because it is the entry
point into the community of users. A screenshot of a community page
served by advisor server 150 is illustrated in FIG. 4B.
[0110] As shown in FIG. 4A, a community page 400 may include
sections tabbed as Tracked 408, Collection 410, Wish List 412, Now
Playing 414, Friends 416, and Forums 418. These features of the
communities within the system and methods of the present invention
are characterized below.
[0111] 1) Tracked 408--allows users to get instant updates on
GameSpot or via email whenever there are any news updates on their
favorite games, either from GameSpot itself or from more the 350
other game sites around the web;
[0112] 2) Collection 410--where users can list all of the games
they own and compare them to other GameSpot users and even get an
estimated value on their game collection. Collections also allow
users to easily rate and keep track of all of their games
[0113] 3) Wish List 412--lets users pick the games they are hoping
to buy in the future. During the holiday season, users' wish lists
will be featured on the front page of GameSpot, enabling gift
givers to easily select, and then instantly order games for
participating friends and family;
[0114] 4) Now Playing 414--allows users to define their "up to the
minute" personal tastes and interests to other community members by
listing their the games they are currently playing;
[0115] 5) Friends 416--knowing that word of mouth is the best way
to get game recommendations, the Friends page helps users reach
each other for insights into popular games, send private messages,
and even find potential online gaming opponents;
[0116] 6) Forums 418--Forums are message boards for users to share
their opinions and thoughts, exchange hints and cheats, and more.
The system of the present invention includes a message board forum
capable of handling more than 200,000 message posts per day. Forums
are provided and linked to from sites located on the user's
personalized home page. The forums may be a single, game-specific
forum per game (irrespective of how many platforms the game is on;
still just one forum), or more global topic forums, depending upon
the user's preferences and usage history.
[0117] 7) Journals 406--Additional features of the Community page
400 include Journal section 406. Journals give each user a personal
soapbox and diary. Journals are intended to foster user loyalty and
engagement with the sites and services produced by the system and
method of the present invention, as well as a manner in which to
foster community amongst users.
[0118] In addition to accessing journals from Community page 400 by
Journal section 406, users can access their own journals from their
user profile pages (for example, profile tab 404), and in turn,
they can reach other users' journals from those users' profile
pages. Additionally, user journals can be accessible from unique
URLs that incorporate usernames. It can also be possible for users
to use RSS to either feed in an existing journal into the present
system or feed a journal out of the system.
[0119] Journals, as used in the system and methods of the present
invention, are similar to flexiform threads, but have additional
characteristics that provide added functionality. A journal is
essentially a message board thread with write access limited to the
specific owner of the journal (the user), and read access based on
the user's profile setting (public, friends only, anonymous).
Journal entries are essentially the same thing as message board
posts, and can have the same properties--users can have access to a
WYSIWIG editor for creating journal entries, and can then edit
those entries using the existing tools. Journals can be paginated
chronologically the same way message board threads already are.
Journal entries should also have the same dropdown options as
message board posts do, allowing readers to report abuse and so
on.
[0120] Some of the additional characteristics of the journals of
the present system that differ from flexiform threads include topic
lines. Each journal entry can have a topic line, identical to when
a user is creating a topic in a forum, as opposed to responding to
a topic. Additionally, users can enable (default) or disable user
comments on journal entries, which can be a new option in the
user's preferences. The "Comments" system replaces the "Reply" and
"Quote Reply" options found in GameSpot forum threads, and allows
readers to respond to journal entries. Comments can be listed as
follows: "Comments (#)", where # is the number of comments that
have already been submitted, e.g., "Comments (5)". Clicking the
comments link next to a journal entry is how you read comments
about the journal entry and/or submit your own. Comments on
journals can be added via a pop-up tool based on a Community
Messenger. Comments are listed in chronological order in a simple
text-based format with the comment itself, the author's username,
and a timestamp for when the comment was posted. The comment
submission field is at the end.
[0121] Individual journal comments optionally can have report-abuse
options, as the report abuse option on the journal entries
themselves can serve well enough for policing comments related to
the journal entry. Journal entries need not have signatures.
However, images and HTML are permitted. Users can extract their
journals from their profile pages, or even import an existing
journal into the system. An option to "Add a link to my journal to
my sig" can also be employed.
[0122] When visiting another user's profile, the Journal tab 406
can be highlighted if the user has posted at least one journal
entry. Also, the user may set an "Allow Comments/Do Not Allow
Comments" parameter via radio buttons (default=comments on), which
can be definable on a post-by-post basis.
[0123] Additionally, at the top of the page, the user is prompted
to name his journal (as though creating a User Created Board), a
parameter that can be save-able but also changeable at any time. By
default, the system can name users' journals "[Username]'s Personal
Journal". On a journal preferences page, this section indicates
"Optional: Please describe yourself or describe what your journal's
about. Your description will be displayed on your journal." If the
user doesn't put anything in his description field, the description
box simply need not appear on his journal pages.
[0124] Journal topics are grouped by date. In keeping with journal
and blogging conventions, topics can be grouped by date (per the
format in the design). So if a user posts two journal up-dates
today, both updates are grouped under the heading of
"Tuesday--August 24, 2004". In turn, individual topics only get a
timestamp. Times can be displayed as "4:36 pm", or as "4:36 PM".
Timezones are selected based on the user's location preference, or
selected from a list.
[0125] Also, journals are subject to the same terms of service and
posting guidelines with regard to content restrictions as typical
posts. Instead of a message saying, "When writing your message,
remember to keep the language clean", the system can include the
following instructional text, such as "This journal is for you to
share or explore your thoughts about gaming or other topics.
However, when writing your entries, please remember to keep the
language clean" or the like.
[0126] When visiting one's own Journal tab 406 subsequent times,
the view can be of the journal entries themselves--that is, the
same view as other users would see, but would include an option to
"Post New Journal Entry" (needs graphic) instead of the usual Post
New Message. Further, journal authors can be allowed to comment on
their own journal entries if desired and if they've enabled
commenting. Users may delete their journal entries one at a time,
and there can be an Are You Sure? prompt prior to deletion.
[0127] The journal can also be surfaced on the user's profile page,
in the Personal Data section, below the About Me
section--especially when looking at profiles for those users who
have posted to their journals.
[0128] The format, when looking at the profile of someone who has
previously posted a journal entry, is as follows in Table 4:
TABLE-US-00004 TABLE 4 Format Example [Journal Name] [GregK's
Personal Journal] [Latest Journal Entry Title] [Revisiting Panzer
Dragoon Orta] Posted [Jun. 25, 2004 3:07 am GMT]
[0129] The latest journal entry title is hyperlinked to the journal
page.
[0130] If looking at the Community page 400 prior to posting a
journal entry for the first time, there appears a "My Personal
Journal" link underneath the "My User-Created Board." The
User-Created Board link and the journal link can be temporary here,
since this box is labeled "My Stats"--The system can fill it with
stats and add another box called "My Forums" for these.)
[0131] 8) Now Playing 414--Additional features of the Community
page 400 include Now Playing section 414. The Now Playing tab 414
automatically lists the games in the user's Now Playing list. If
the user has nothing on his Now Playing list, this tab section is
grayed out. This box stretches vertically based on the total number
of games in a user's Now Playing list.
[0132] 9) Friends' Journals 416--This tab automatically surfaces
the usernames or icons of up to eight friends--specifically, up to
eight friends that have most recently updated their journals. So,
even if I have 50 friends, whoever among them updated their
journals most recently are going to be the friends who show up on
my list. Users who set their journals to NOT be publicly viewable
are automatically excluded from these lists.
[0133] Preferably, users who set their journals to "Friends Only"
are displayed in these lists expressly to those who are their
friends. For example, if Steve, Trey, and JSD are all friends, then
they can see each other on their friends lists. Greg, who is
friends only with Steve, couldn't see Trey's and JSD's journals
from Steve's journal, however. Alternatively, the system may post
an error message for users trying to access restricted journals.
Generally, restricted journals have their tabs grayed out. If I
visit your profile and you have a journal, but it's for friends
only and I'm not your friend, then I see a grayed out journal
tab.
[0134] Additional Community Features
[0135] The Community front door provides an entry point into pages
in which like users meet and interact, but importantly the
community of users provides the collaborative data with which the
ranked list of recommended products is compiled. The community as
an entity is formed by a series of new, personalized pages produced
by the system and method of the present invention by the
overarching "community" framework that exposes trends and
accomplishments within the collection of users who opt to
participate (also know as "GameSpot Community"). The community is
concisely presented by way of personalized and customized options
to the user, including existing download and media preferences and
account settings, as well as additional settings.
[0136] The advisor server 150 provides a gateway hub from which
users can access the individual components of their community pages
as well as find other users' pages as well as see various
interesting statistics about the community. These statistics
include, for example, total number of members (i.e., number of
basic and number of complete members can be surfaced), total number
of members currently online, member of the week, (spotlighting a
key member's profile and granting that member the top games on his
wish list). Also, the most owned and most wanted games by platform
is also displayed, based on users' game collections and most wanted
lists. Additional community statistics compiled and displayed
include the most popular forums and forum threads and a color-coded
world map showing where GameSpot users are concentrated.
[0137] Announcements
[0138] As also shown in FIG. 4A, Announcements box 432 employs a
User Interface so that the community manager can update it
frequently. The User Interface is functionally similar to a journal
User Interface, but the Announcements box 432 has the ability to
float announcements (e.g., the "Terms of Service" announcement can
always be on top). Also like journal entries, announcements carry a
timestamp for context. For end users, there is also navigation
capabilities at the bottom of the scroll box to flip through
"previous>>" announcements.
[0139] Search
[0140] The search field 434 includes radio buttons beneath the
search field 434 to allow the user to choose the destination for
his search from GameSpot 436 (by default), Message Boards 438, and
Users 440. These options can work intuitively; the default search
is equivalent to initiating a search from the main GameSpot
page.
[0141] My Info
[0142] The field labeled "My Stats" can have its name changed to My
Info 442. The My Info box 442 can list the user's username and
icon; however, the dimensions of the My Info box 442 can change to
a wide-and-short rectangle; the username can appear directly above
the avatar, with both left justified in the box.
[0143] The middle of the My Info box 442 is an
automatically-scrolling, automatically-wrapping statistics box with
the heading "Vital Stats". Users can increase the speed of the
scrolling by mousing over the box. The contents can include the
following fields: Level, Percent to Next Level, Current Rank, Next
Rank, Last Online, Most Visited Forum, Total Forum Posts, Total
Messages Read, Total Number of Messages Edited, Total Time Online,
Preferred Genre, Total Number of Games Rated, Total Number of Games
Reviewed, Average Game Rating, Total Number of Private Messages
Sent, Member Since, Community Ranking, Number of Thumbs Ups,
Average Number of Visits Per Week, Total Number of Friends, Total
Number of Threads Locked, Next Game on Wish List, Total Number of
Tracked Games, Total Number of Games in Collection, Total Number of
Games in Wish List, Total Number of Games Now Playing, Average
Number of Pages Per Visit, Total Number of Private Messages
Received, Estimated Value of Collection, Most Recent Emblem, Number
of Trusters, Total Number of Threads Moderated, Most Pages Visited
Per Session, Most Visited Content on GameSpot, and Total Visits to
GameSpot.
[0144] The statistics are compiled based on the behavior of
GameSpot visitors as they navigate the site, update their
biographical information, provide ratings of products, share
information, and interact in the community. These data are then
used by the advisor server to return a ranked recommended list of
products to users.
[0145] Community Reviews
[0146] As illustrated in FIGS. 5A-5C, one method of providing
guidance and recommendations to users is by way of reader reviews,
or more broadly Community Reviews. Community Reviews provide
insight and recommendations from users 507 to users regarding a
variety of products. Registered users can submit reviews and review
forum posts to include a button-based Thumbs Up/Thumbs Down voting
system 509. Anonymous or unregistered users attempting to vote are
taken to a basic sign-up page to register so that they may vote.
Once a user has voted on a post or a review, a Thank You message
appears instead of the vote prompt.
[0147] Users with the greatest number of Thumbs Up votes for either
their posts or their reviews earn unique emblems respective to
posts or reviews. Emblems are listed and described further in
Appendix B. There are three levels of emblem: Top 100, Top 500, and
Top 1,000. These emblems are mutually exclusive to each other. In
addition to earning emblems on their profile pages, users to whom
votes are cast also gain a symbol next to their username. These
symbols say "top 100", and the like, depending upon the level.
These symbols then follow the user and appear wherever these users
post materials.
[0148] On a community review index page, 10 percent of the total
reviews (rounded to the nearest whole number, e.g. if there are 15
reviews, then 10 percent=2 reviews) become "featured reviews".
Featured reviews 511 are at the top of the page and gain that
status from user voting; the review with the most Thumbs Up votes
is the top review. Remaining reviews can appear in a "Latest
Reviews" section 513 beneath the Featured Reviews 511. At the
bottom of a community review, Featured Reviews 511 and up to three
Latest Reviews 513 are listed. If the community review itself is
one of the Featured Reviews 511 or one of the top three Latest
Reviews 513, then the reference to it can be omitted from listings
at the bottom.
[0149] A fairly prominent button entitled "Read More Reviews of
this Game on GameFAQs.com" 515, can link to the respective reader
review index page on GameFAQs. This button 515 appears on community
review index pages as well as at the bottom of individual community
reviews. Community reviews are functionally similar to message
board posts. That is, the reviews can be administered, reported, or
edited.
[0150] When a user elects to write a review (FIG. 5C), in addition
to rating the game and writing the review, the user can fill in the
following fields via drop-down menus 531, 533, 535:
[0151] Difficulty 531 (Very Easy, Easy, Just Right, Hard, Very
Hard)
[0152] Learning Curve 533 (0 to 30 Minutes, 30 to 60 Minutes, 1 to
2 Hours, 2-4 Hours, 4 or More Hours)
[0153] Time Spent Playing 535, to Date (10 Hours or Less, 10 to 20
Hours, 20 to 40 Hours, 40 to 100 Hours, 100 or More Hours)
[0154] Additionally, a reviewer may be prompted by the system to
enter a review summary 537, equivalent to the topic of a forum
thread. The review summary 537 may then appear on review summary
pages. The review summary is limited to 30 words. At the top of the
review summary pages, there are four pie charts 555, 557, 559, 561,
respectively displaying Score Breakdown (based on score ranges)
555, Difficulty Breakdown 557, Learning Curve Breakdown 559, and
Time Spent Breakdown 561, based on stats from reader review
submissions. The pie charts 555, 557, 559, 561 provide a quick
summary to a user glancing at the review pages.
[0155] Community User Ratings
[0156] In order to facilitate further interaction within the
community of users, and in order to refine ranked recommended
product offerings, a reader rating system is used to evaluate and
rate products. As shown in FIGS. 6A-6D, the community user ratings
are a Flash-based unit, allowing the user to use a slider 606 to
assign a score between 1.0 and 10 and then click "Go" 608 to lock
in the score. The pluses 610 and minuses 612 on opposite sides of
the sliding scale can increase the score in increments of 0.1. The
community score 614 (i.e., average user rating) and corresponding
one-word descriptor can change in real time as the user manipulates
the sliding scale.
[0157] The pointer on the slider defaults to indicating the point
on the scale that corresponds to the community score as shown in
FIG. 6A (Example 1). If no one has rated a game yet, then the
player score appears null, and the pointer on the slider defaults
to the 7.0 "redline" on the scale as shown in FIG. 6B (Example 2).
After a user has rated a game, his score is displayed beneath the
sliding scale, and the "Go" button is replaced with a "Reset Your
Score" button 616 as shown in FIG. 6C (Example 3). Clicking on the
"Reset Your Score" button 616 omits the user's score from the
database and reverts to an Example 1 (shown in FIG. 6A) treatment,
as though the reviewer had not rated the game yet.
[0158] The system of the present invention allows the ability to
surface a pop-up version of this flash unit (or some other, similar
solution) elsewhere on the site--specifically, from a user's
Collection pages, where they are invited to "Rate it!" for each
game they own.
[0159] If a game has not yet been officially released (that is, the
game's release date is in the future), the reader scoring system
component does not appear and the Add to Collection and Now Playing
options are unavailable as shown in FIG. 6D (Example 4). Further,
if a user has not yet registered or is anonymous, the Add to
Collection and Now Playing options are grayed out if a game's
release date is in the future.
[0160] The system includes the ability to remove games from lists
in the same way as they can be added, wherein minus graphics can
replace the plus graphics in those cases as shown in FIGS. 6A and
6B (examples 1 and 2).
[0161] A "Quick Stats" section 618 illustrates community stats
detailing community activity at the game level. For all games, an
overall ranking can be assigned, ranging from the #1 game on down,
based on total number of games in the system database as shown in
FIGS. 6A-6D. The ranking also indicates the extent to which the
ranking has changed recently, by noting how many (if any) ranks the
game jumped up or down in the last day.
[0162] For games that are available, the system lists how many
users have the games in their collections and in their now playing
lists, as shown in FIGS. 6A-6C (examples 1, 2, and 3). These
declarations can be hyperlinked to emblem-style lists of those
users. The system can paginate such pages, to display, for example,
200 users at a time.
[0163] As shown in FIG. 6D, for games that are not yet available,
the system can declare how many users have the particular game in
their wish lists (but not tracked games lists). These declarations
can also be hyperlinked to emblem-style lists of those users,
paginated, and displayed as well.
[0164] My Game Collection and My Most Wanted (Games)
[0165] The Game Collection & Most Wanted page can offer
GameSpot users a free, personalized service by which users can
maintain a list of the games they own and want to own, and have
automatic access to a number of unique features and statistics
concerning their lists. The My Game Collection & My Most Wanted
gives users the ability to easily build their game collection list
and game wish list and to keep track of the games on those lists.
The My Game Collection & My Most Wanted pages are publicly
visible (by default), so users can exchange links to them for
bragging rights, and can also readily access useful information
about the games they own or plan to own. For example, the system of
the present invention keeps track of statistics, and can feature an
ongoing "Win your Most Wanted" contest to entice users into using
the service.
[0166] An exemplary embodiment of the present invention includes a
method in which users can build their game collections on GameSpot.
In the My Games & Preferences page, another gateway link takes
users directly to the "My Game Collection" section of the My Games
& Preferences. This link and page surfaces a search box
labeled, "Add Games to Your Collection." Search options, such as
"Search by Title" and other criteria for sorting the search results
are employed, such as community ratings, number of discussions in
the forums, and the like. When the Search Results are displayed, an
"I own this game, Add it to my collection" button is used to
automatically add games that the user owns whose release date is
less than or equal to today's date (i.e., the games are available).
Alternatively, a button called "I want this game, Add it to my wish
list" appears for games that the user would like to own. A small
pop-up window is included to confirm the user's action. If a user
has a game in his collection, neither button need appear, and the
system shows a message button such as "You own this game" or "This
game is on your wish list" depending upon the status of the game.
Clicking any of that message text button takes the user to his
collection page. If a user has a game in his wish list, and the
game is available, the collection button appears. Adding a wish
list game to a collection automatically removes the game from the
user's wish list. To safeguard the lists, games may only be remove
from a collection from the collection page.
[0167] Also, the system can also give users the option to import a
collection list from another source, such as a web page or other
network document. Users can plug in a URL or paste in a text
document with a games list that the system can parse and interpret
and use to add games to the respective lists.
[0168] For example, a user can select the "Import Your Game
Collection from a Web Page", such as an IGN user page that they've
already built, or a forum post they've created. The system queries
the web page or document for game titles listed using delimited
text, paragraph breaks, commas, spaces, tables, and the like. The
system automatically adds the located game titles to a user's game
collection. A one-step approval process occurs first, which allows
the user to uncheck any games that were improperly added (e.g.,
multiple versions of multiplatform games). The user then can
continue to add games manually via additional searches.
[0169] As an alternate importing method allows users to enter the
12-digit UPC that appears with the bar code on the back of every
retail game. UPC data is already being collected, but UPC data for
multiple versions of a game can also be stored. For example, Halo
for the Xbox was released in two editions--the software is
identical, but the Game of the Year packaging has a different UPC
than the original release. Additionally, the system can store UPC
data for foreign versions of games.
[0170] Similarly, multiple versions of the same game may also be
stored in the appropriate user list. For example, the Japanese
version of a game is oftentimes different than its domestic
release. In order to cater both to the importer market as well as
foreign users, the system of the present invention allows users to
select which version of a game they have. Someone who was a gaming
devotee may have imported a game and then purchased its domestic
counterpart. This user would want to show those differences and the
multiple versions as part of their collection. Thus, two entries
for the same game are possible, provided those entries refer to
different versions of the game. If the UPC for the foreign release
is not available, the system offers a "Can't find your game in our
system? Contact us!" link on the collection page that enables a
user to send an e-mail to the data group producing the system of
the present invention. The system also solicits users for some of
the missing data (e.g., foreign UPCs) at this point.
[0171] Users may also designate a subset of games in their
collection as games they're "Now Playing." This list shows up at
the top level of a user's public profile. Up to ten games may be
designated as "now playing." The system of the present invention
factors game rentals into this list as well.
[0172] Once the user builds a My Game Collection or a Most Wanted
list, the user can customize the design of the My Game Collection
page or the Most Wanted list page. For example, these pages can
take the same basic design as for Search, because they can serve a
similar purpose--to point the user to the system resources for
those games, as well as to provide useful and interesting
at-a-glance information about each game. The system allows the user
to customize the fields that appear on the page by turning on or
off a check-boxed row of possible data types. Displayed columns can
be shifted left or right. Users may also restore a default view if
they decide to abandon their changes.
[0173] The My Collection list and the Wish List are sortable by the
listed fields, and a dropdown box or similar item can let users set
the list to display games from one platform. Another similar
checkbox is available to "show only online games." The following
list of fields are available including, Game Name (clicking on this
field takes the user to the gamespace), Platform, Publisher,
Developer, Territory/Region, Genre, Release Year, Release Date,
GameSpot Review Score (clicking on this field takes the user to the
review pages), Reader Review Score (clicking on this field takes
the user to a reader review index), User's Personal Review Score
(clicking on this field takes the user to user's review, or to a
"review it" page if the user hasn't reviewed that game yet), Number
of Players, Last Update (refers to the post date and story type of
most recent story in gamespace), Online (Y/N), Completed (Y/N),
Number of GameSpot Users That Own This Game (clicking on this field
takes the user to a list of users, sorted alphabetically, that own
this game), and Overall Rank of Game (the higher the number of
users claiming to own this game is, the higher its rank).
[0174] Additionally, the system automatically tabulates the
following measures for each user's collection, including Total
Games in Collection, Estimated Value of Collection, Average
GameSpot Score of Collection, Average Reader Score of Collection,
Average Game Rankings Score of Collection, Preferred Types of
Games, Owned Gaming Platforms, Preferred Gaming Platform, Oldest
Game Owned, Newest Game Owned, and Last Game Added.
[0175] The system can automatically tabulate the following for each
user's wish list, including Most Wanted Collection Stats, Total
Games in Most Wanted, Estimated Cost of Most Wanted, and Estimated
Cost of Most Wanted (with discounts or other special offers).
[0176] The system also provides graphically (e.g., bar graph or pie
chart, or the like) the following analysis, including Breakdown of
games by platform, Breakdown of games by genre, and Breakdown of
games by year of release.
[0177] Using the Game Collection and Wish Lists, system-wide
statistics are available, including stat lists such as Most Owned
games (clicking on this name field takes the user to a list of
users that own the game), Most Wanted Games (the game with the most
wish list appearances leads here--clicking on a name field here
takes the user to a list of users that want the game), Largest
Collection (shows users with the most games), Most Owned Platform,
Most Owned Publisher, Most Valuable Collection (can include retail
prices for old and/or foreign games), Most Played Game (highest
number of current "Now Playing" appearances wins.
[0178] Additionally, the Game Collection and Wish Lists collections
enables a Game Collection Image where the system of the present
invention enables users to display a digital photo of their game
setups and/or game collections by uploading those photos to this
space.
[0179] Once the statistics are compiled by the system of the
present invention, users may communicate with each other, and the
system may facilitate communication between users with similar
tastes by analyzing the Game Collection and Wish Lists and
demographic and behavioral statistics. For example, if two users
with public collections have X percentage of games in common (e.g.,
50 percent of the smaller collection's games, though the number
must be at least 10 games to prevent people from entering one
popular game and suddenly being bombarded with every list in the
system), the system invites them to look at each others' pages,
send each other a nice note, leave feedback on that user, and so
on. Whenever one user is looking at other user's collection, games
that are in the first user's collection are highlighted. This
highlighting feature, combined with the ability to show online
games, allows for users to find online games more easily, thereby
facilitating two previously unknown users to play together.
[0180] My Reader Reviews & FAQs (i.e., My Contributions)
[0181] The system can list the games for which the user has reader
reviews and/or frequently asked questions (FAQs) posted. The system
can also surface reader reviews for an individual user that were
not posted. Users can edit their reader reviews, but the re-posted
reader reviews will indicate the time when the review was last
edited.
[0182] Other users can be able to give reader review a "Thumbs Up"
if they found the reader's review useful. Reviews with the greatest
number of Thumbs Ups can float to the top of a games-pace's reader
review list. Users who earn the greatest number of thumbs ups
across their reviews receive special privileges as incentive to
post reviews. Users may also indicate that they "Trust This
Reviewer". The system will automatically notify this user when the
"trusted" reviewer posts additional messages or reviews. Also, the
"Trusted By # GameSpot Community Members" statistic can appear on
the trusted reviewer's Reader Review page.
[0183] If a user has posted no reader reviews, he will be invited
to write a review for games in his collection. An explanatory
paragraph can enlighten users as to what reader reviews are all
about and why they're useful.
[0184] Game Collection
[0185] With regard to the feature above where a user builds a game
collection, on the My Games & Preferences page, the system may
surface a search box labeled, "Search for Games to Add Them to Your
Collection." On Search Results, in addition to a "track it" button,
an "I own this game" button can be added to facilitate population
of a user's product lists of products that they already own and a
user's wish list. These tracking and ownership buttons may also be
shown in other features, such as in the review section, where a
user reads reviews of various products.
[0186] Additionally, users can populate their game collection list
by importing lists from other sources. That is, a button labeled
"Import Your Game Collection from a Web Page" enables the present
invention to query a web page that a user may have previously
created for all game titles. Once the game titles are located,
acquisition module 152 acquires the game titles and automatically
adds those titles to a user's game collection list. The process may
include an approval process, which would allow the user to remove
any games that were improperly added, and a manual step to permit
the user to add games manually.
[0187] Any number of sorting and filtering options are provided
where the user can manipulate the game collection list.
Additionally, a user has the ability to easily rate each game in
the collection. The system can tally total number of games, by
platform and overall, and also estimate the total value of a user's
game collection based on game MSRP (or perhaps, more accurately,
based on used game prices).
[0188] Game collection statistics are tallied including the Total
Games in Collection, Estimated Value of Collection, Average
GameSpot Score of Collection, Average Reader Score of Collection,
Preferred Genres, Owned Gaming Platforms, Oldest Game Owned, Newest
Game Owned, and the like.
[0189] The devices and subsystems of the exemplary embodiments of
FIGS. 1-6 are for exemplary purposes, as many variations of the
specific hardware used to implement the exemplary embodiments are
possible, as will be appreciated by those skilled in the relevant
arts. For example, the functionality of one or more of the devices
and subsystems of the exemplary embodiments of FIGS. 1-6 can be
implemented via one or more programmed computer systems or
devices.
[0190] To implement such variations as well as other variations, a
single computer system can be programmed to perform the special
purpose functions of one or more of the devices and subsystems of
the exemplary embodiments of FIGS. 1-6. On the other hand, two or
more programmed computer systems or devices can be substituted for
any one of the devices and subsystems of the exemplary embodiments
of FIGS. 1-6. Accordingly, principles and advantages of distributed
processing, such as redundancy, replication, and the like, also can
be implemented, as desired, to increase the robustness and
performance of the devices and subsystems of the exemplary
embodiments of FIGS. 1-6.
[0191] The devices and subsystems of the exemplary embodiments of
FIGS. 1-6 can store information relating to various processes
described herein. This information can be stored in one or more
memories, such as a hard disk, optical disk, magneto-optical disk,
RAM, and the like, of the devices and subsystems of the exemplary
embodiments of FIGS. 1-6. One or more databases of the devices and
subsystems of the exemplary embodiments of FIGS. 1-6 can store the
information used to implement the exemplary embodiments of the
present invention. The databases can be organized using data
structures (e.g., records, tables, arrays, fields, graphs, trees,
lists, and the like) included in one or more memories or storage
devices listed herein. The processes described with respect to the
exemplary embodiments of FIGS. 1-6 can include appropriate data
structures for storing data collected and/or generated by the
processes of the devices and subsystems of the exemplary
embodiments of FIGS. 1-6 in one or more databases thereof.
[0192] All or a portion of the devices and subsystems of the
exemplary embodiments of FIGS. 1-6 can be conveniently implemented
using one or more general purpose computer systems,
microprocessors, digital signal processors, micro-controllers, and
the like, programmed according to the teachings of the exemplary
embodiments of the present invention, as will be appreciated by
those skilled in the computer and software arts. Appropriate
software can be readily prepared by programmers of ordinary skill
based on the teachings of the exemplary embodiments, as will be
appreciated by those skilled in the software art. Further, the
devices and subsystems of the exemplary embodiments of FIGS. 1-6
can be implemented on the World Wide Web. In addition, the devices
and subsystems of the exemplary embodiments of FIGS. 1-6 can be
implemented by the preparation of application-specific integrated
circuits or by interconnecting an appropriate network of
conventional component circuits, as will be appreciated by those
skilled in the electrical arts. Thus, the exemplary embodiments are
not limited to any specific combination of hardware circuitry
and/or software.
[0193] As stated above, the devices and subsystems of the exemplary
embodiments of FIGS. 1-6 can include computer readable media or
memories for holding instructions programmed according to the
teachings of the present invention and for holding data structures,
tables, records, and/or other data described herein. Computer
readable media can include any suitable medium that participates in
providing instructions to a processor for execution. Such a medium
can take many forms, including but not limited to, non-volatile
media, volatile media, transmission media, and the like.
Non-volatile media can include, for example, optical or magnetic
disks, magneto-optical disks, and the like. Volatile media can
include dynamic memories, and the like. Transmission media can
include coaxial cables, copper wire, fiber optics, and the like.
Transmission media also can take the form of acoustic, optical,
electromagnetic waves, and the like, such as those generated during
radio frequency (RF) communications, infrared (IR) data
communications, and the like. Common forms of computer-readable
media can include, for example, a floppy disk, a flexible disk,
hard disk, magnetic tape, any other suitable magnetic medium, a
CD-ROM, CDRW, DVD, any other suitable optical medium, punch cards,
paper tape, optical mark sheets, any other suitable physical medium
with patterns of holes or other optically recognizable indicia, a
RAM, a PROM, an EPROM, a FLASH-EPROM, any other suitable memory
chip or cartridge, a carrier wave, or any other suitable medium
from which a computer can read.
* * * * *