U.S. patent application number 11/780985 was filed with the patent office on 2009-01-22 for search using multi-faceted reputation information.
This patent application is currently assigned to EBAY Inc.. Invention is credited to Marc Delingat, Snezana Sahter, Liangjie Xu.
Application Number | 20090024402 11/780985 |
Document ID | / |
Family ID | 40265539 |
Filed Date | 2009-01-22 |
United States Patent
Application |
20090024402 |
Kind Code |
A1 |
Delingat; Marc ; et
al. |
January 22, 2009 |
SEARCH USING MULTI-FACETED REPUTATION INFORMATION
Abstract
A method and a system for searching objects using reputation
information are provided. Example embodiments may include
presenting multiple reputation dimensions and multiple attributes
related to each of the reputation dimensions to a user. The method
may also include detecting user selections of reputation dimensions
and attributes related to the reputation dimensions and including
selected attributes related to the reputation dimensions as
criteria parts of search queries. Some example embodiments may
include conducting a search of a database of objects using the
search query to generate search results.
Inventors: |
Delingat; Marc; (Mountain
View, CA) ; Sahter; Snezana; (San Jose, CA) ;
Xu; Liangjie; (Saratoga, CA) |
Correspondence
Address: |
SCHWEGMAN, LUNDBERG & WOESSNER/EBAY
P.O. BOX 2938
MINNEAPOLIS
MN
55402
US
|
Assignee: |
EBAY Inc.
San Jose
CA
|
Family ID: |
40265539 |
Appl. No.: |
11/780985 |
Filed: |
July 20, 2007 |
Current U.S.
Class: |
705/310 |
Current CPC
Class: |
G06Q 30/04 20130101;
G06F 16/24575 20190101; G06F 16/2425 20190101; G06F 16/242
20190101; G06F 16/2455 20190101; G06Q 50/184 20130101 |
Class at
Publication: |
705/1 |
International
Class: |
G06Q 30/00 20060101
G06Q030/00; G06F 17/30 20060101 G06F017/30; G06F 17/40 20060101
G06F017/40; G06Q 10/00 20060101 G06Q010/00 |
Claims
1. A method comprising: presenting a plurality of reputation
dimensions to a user; presenting a plurality of attributes related
to each of the plurality of reputation dimensions to the user;
detecting a user selection of a selected reputation dimension of
the plurality of reputation dimensions and a selected attribute
related to the selected reputation dimension; including the
selected attribute related to the selected reputation dimension as
a criterion part of a search query; and conducting a search of a
database of objects using the search query to generate search
results.
2. The method of claim 1, comprising sorting the search results,
using the selected reputation dimension; and displaying the sorted
search results.
3. The method of claim 2, comprising providing a notification
message when an attribute of a reputation dimension other than the
selected reputation dimension transgresses a threshold.
4. The method of claim 1, wherein the selected reputation dimension
includes transaction participation aspects for which feedback
information is stored in a database.
5. The method of claim 1, wherein the selected attribute related to
the selected reputation dimension includes feedback ratings and
comments corresponding to the selected reputation dimension.
6. The method of claim 4, comprising receiving detailed feedback
ratings by requesting a feedback giver to respond to specific
questions relating to certain transaction participation
aspects.
7. The method of claim 1, wherein the plurality of reputation
dimensions include reputation dimensions related to a marketplace
participant.
8. The method of claim 1, comprising using the criterion part of
the search query to filter the database of objects in order to
limit a number of objects included in the search results.
9. The method of claim 1, wherein the plurality of attributes
related to each of the plurality of reputation dimensions include
feedback ratings.
10. A system comprising: a user interface module to present a
plurality of reputation dimensions to a user, and to present a
plurality of attributes related to each of the plurality of
reputation dimensions to the user; a detection module to detect a
user selection of a selected reputation dimension of the plurality
of reputation dimensions and a selected attribute related to the
selected reputation dimension; a database to maintain data related
to a plurality of objects and reputation information; and a search
engine to include the selected attribute related to the selected
reputation dimension as a criterion part of a search query, and to
conduct a search of the database using the search query to generate
search results.
11. The system of claim 10, comprising a sort module to sort the
search results, using the selected reputation dimension.
12. The system of claim 11, comprising a notification module to
provide a notification message when an attribute of a reputation
dimension other than the selected reputation dimension transgresses
a threshold.
13. The system of claim 11, wherein the user interface module is to
display the sorted search results.
14. The system of claim 10, wherein the database is to maintain the
reputation dimension including transaction participation aspects
for which feedback information is stored in the database.
15. The system of claim 10, wherein the detection module is to
detect the selected attribute related to the selected reputation
dimension including feedback ratings and comments corresponding to
the reputation dimension.
16. The system of claim 10, wherein the user interface module is to
receive detailed feedback ratings by requesting a feedback giver to
respond to specific questions relating to certain transaction
participation aspects.
17. The system of claim 14, wherein the user interface module is to
present the plurality of reputation dimensions including reputation
dimensions related to a marketplace participant.
18. The system of claim 10, wherein the search engine is to use the
criterion part of the search query to filter the database of
objects in order to limit a number of objects included in the
search results.
19. The system of claim 10, wherein the user interface module is to
present the plurality of attributes related to each of the
plurality of reputation dimensions including feedback ratings.
20. A system comprising: means for presenting a plurality of
reputation dimensions to a user; means for presenting a plurality
of attributes related to each of the plurality of reputation
dimensions to the user; means for detecting a user selection of a
selected reputation dimension of the plurality of reputation
dimensions and a selected attribute related to the selected
reputation dimension; means for including the selected attribute
related to the selected reputation dimension as a criterion part of
a search query; and means for conducting a search of a database of
objects using the search query to generate search results.
21. The system of claim 20, comprising means sorting the search
results, using the selected reputation dimension; and displaying
the sorted search results.
22. The system of claim 20, comprising providing a notification
message when an attribute of a reputation dimension other than the
selected reputation dimension transgresses a threshold.
23. A machine-readable medium comprising instructions, which when
implemented by one or more processors perform the following
operations: presenting a plurality of reputation dimensions to a
user; presenting a plurality of attributes related to each of the
plurality of reputation dimensions to the user; detecting a user
selection of a selected reputation dimension of the plurality of
reputation dimensions and a selected attribute related to the
selected reputation dimension; including the selected attribute
related to the selected reputation dimension as a criterion part of
a search query; and conducting a search of a database of objects
using the search query to generate search results.
24. The machine-readable medium of claim 23, comprising
instructions, which when implemented by one or more processors sort
the search results, using the selected reputation dimension; and
displaying the sorted search results.
25. The machine-readable medium of claim 23, comprising
instructions, which when implemented by one or more processors
provide a notification message when an attribute of a reputation
dimension other than the selected reputation dimension transgresses
a threshold.
Description
TECHNICAL FIELD
[0001] Example embodiments relate generally to the technical field
of data management, and in one specific example, to a system for
performing search using multifaceted information.
BACKGROUND
[0002] The Internet technologies and their widespread use have made
it possible for many people to participate in online trade
activities. Many companies facilitate trade on servers connected to
users over one or more networks, typically including the Internet.
The users buying and/or selling items over these networks loosely
comprise a marketplace community within an electronic environment.
A distinction between non-electronic selling practices such as
traditional stores and current electronic selling mechanisms is the
component of anonymity inherent in an electronic environment, which
is not always conducive to forming a trusting environment in which
two or more users wish to form a business relationship.
[0003] To overcome some reservations about the anonymity component
within the electronic marketplace community and to provide
incentives for participating in transactions within electronic
marketplaces, Internet marketplaces, such as auction sites run by
eBay, Inc. of San Jose, Calif., provide feedback ratings generated
from feedback between users. A user's feedback rating may indicate
the user's reputation within the electronic community and provides
some indication of the trustworthiness and responsiveness of that
user. A representation of a user's feedback rating may be displayed
along with a business transaction request by the user.
[0004] Feedback ratings may provide a useful mechanism for
indicating a level of user's trustworthiness or past participation
within an electronic commerce forum. Users desire to increase their
feedback ratings because they are one indication of a user's
reputation in the electronic community, and users with high
feedback ratings may enjoy expanded opportunities to transact
business and obtain higher profits or access to more goods and
services. To further motivate the earning of a high feedback
rating, some marketplace providers give awards or identify the
users whose feedback ratings have reached a certain value, or who
are among some number of users with the highest feedback
ratings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Some embodiments are illustrated by way of example and not
limitation in the figures of the accompanying drawings in
which:
[0006] FIG. 1 is a high level diagram depicting an example
embodiment of a system for conducting multifaceted search for
objects using reputation information;
[0007] FIG. 2 is a block diagram illustrating an example embodiment
of a multifaceted search system using reputation information;
[0008] FIG. 3 is a flow diagram illustrating an example embodiment
of a method of searching for objects using reputation
information;
[0009] FIG. 4 is a flow diagram depicting an example embodiment of
a method for sorting the search results of the method of FIG.
4;
[0010] FIG. 5 is a diagram illustrating in an example embodiment of
sets of reputation dimensions associated with sellers, buyers, and
service providers;
[0011] FIG. 6 is a screen shot illustrating an example embodiment
of a user interface including reputation dimensions in search
options;
[0012] FIG. 7 is a screen shot illustrating an example embodiment
of a user interface including reputation dimensions in the search
options and displaying search results sorted based on selected
reputation dimensions;
[0013] FIG. 8 is high level block diagram illustrating an example
embodiment of a network-based commerce system, having a
client-server architecture, using reputation information for
multifaceted search for objects;
[0014] FIG. 9 is an example set of marketplace and multifaceted
search applications used by the network-based commerce system of
FIG. 8; and
[0015] FIG. 10 is a block diagram illustrating a diagrammatic
representation of a machine in the example form of a computer
system.
DETAILED DESCRIPTION
[0016] Example methods and systems for searching for objects using
reputation information have been described. In the following
description, for purposes of explanation, numerous specific details
are set forth in order to provide a thorough understanding of
example embodiments. It will be evident, however, to one skilled in
the art that the present invention may be practiced without these
specific details.
[0017] For the purpose of present application, the term "reputation
dimension" shall be taken to include, but not be limited to,
various aspects of reputation information associated with an entity
participating in an activity (e.g., overall performance, cost of
shipping, timeliness, communication, quality of advertisements,
quality of listing descriptions, quality of packaging, quality of
services provided, and the like).
[0018] Some embodiments described herein may include searching
databases of objects (e.g., items, services, etc.) using some
reputation dimensions and their related attributes (e.g., feedback
scores, percentage ratings, overall feedback ratings such as a
weighted average of feedback scores, positive and negative
comments, etc.) as part of search query. The feedbacks received
from trading parties may be analyzed and the result of the analysis
(e.g., in the form of attributes of the reputation dimensions) may
be presented to users for selection. The selected reputation
dimensions and related attributes may then be included in the
search criteria. This refinement of search may be conducive to
enhancement of the user's confidence in certain qualifications of a
third party (e.g., a potential trading party).
[0019] In some example embodiments, a method may include presenting
multiple reputation dimensions and attributes, related to each of
the reputation dimensions, to users. The reputation dimensions may
include the reputation dimensions related to a marketplace
participant (e.g., seller, buyer, service provider, or client) or
participant in some other network-based activity (e.g., online
gaming, social or business networking etc.). A method may also
include detecting user selections of a reputation dimensions and
attributes related to the reputation dimension.
[0020] The selected attributes related to reputation dimensions may
then be included as a criterion part of a search query when
conducting a search of a database of objects using the search query
to generate search results. The criterion part of the search query
may be used to filter the database of objects in order to limit the
number of objects included in the search results.
[0021] In an example embodiment, a method may include sorting the
search results, using a selected reputation dimension (e.g.
selected by a user from a list of reputation dimensions presented
to the user) and displaying sorted search results. An example
method may include providing a notification message to the user
when an attribute of a reputation dimension other than the
reputation dimensions selected by the user transgresses a threshold
(e.g., one of the feedback ratings or an overall feedback rating
falls below a predefined lower limit or exceeds a predefined higher
limit).
[0022] According to some example embodiments, a reputation
dimension may include transaction participation aspects for which
feedback is available (e.g., overall performance, cost of shipping,
timeliness, communication, quality of advertisements, quality of
listing descriptions, quality of packaging, quality of services
provided, and the like). A selected attribute related to a
reputation dimension may include feedback ratings and comments
corresponding to the reputation dimension (e.g., feedback scores,
percentage ratings, overall feedback rating, positive and negative
comments, etc.).
[0023] In one example embodiment, a method may include receiving
detailed feedback ratings by requesting a feedback giver to respond
to specific questions relating to certain transaction participation
aspects (e.g., what aspect of the shipping and handling the
feedback giver was least satisfied with, or what specific
qualification of a seller the feedback giver appreciates the most,
etc.). This kind of granular feedback may be useful for a user to
obtain a better understanding of the qualifications of a respective
trading party.
[0024] FIG. 1 is a high level diagram depicting an example
embodiment of a system 100 for conducting multifaceted search for
objects using reputation information. The system 100 may include a
user 110, a user computer 120, a server 170, a network 180 and a
user interface 130. The user computer 120 is linked to the server
170 via the network 180 (e.g., the Internet). The server 170 may
include a database of objects that the user 110 may be interested
in searching.
[0025] The user 110 may use the user computer 120 to go online and
provide input to a page provided by the server 170 to search for an
object. The example user interface 130 may be provided by the
server 170 to the user 110 to search for an object using reputation
information. The user interface 130 depicts a search-box 140,
multiple reputation dimensions 150, and list-boxes 190, which may
list attributes 160 related to each of the reputation dimensions
150.
[0026] The user 110 may select any of the reputation dimensions 150
to be used in the search for the object. In addition, in the
list-boxes 190, under each selected reputation dimension(s) 150,
the user 110 may select any attributes 160 related to the selected
reputation dimensions 150 that the user may want to be used for the
search of the object. The server 170 may use the selected
reputation dimensions and the selected attributes related to the
selected reputation dimensions as a criterion part of a query used
to search for the object.
[0027] In an example embodiment, the object may be an item (e.g., a
data item or a described physical item) or a service. The object
may also be listed in an online marketplace, for example. The
reputation dimension 150, for example, may include overall
performance, cost of shipping, timeliness, communication, quality
of advertisement, quality of a listing description, quality of
packaging, quality of service provided and the like. Reputation
dimension attributes 160 may include feedback scores, percentage
ratings, overall feedback ratings such as a weighted average of
feedback scores, positive and negative comments, etc.
[0028] FIG. 2 is a block diagram illustrating an example embodiment
of a multifaceted search system 200 using reputation information.
The search system 200 may include a user interface module 210, a
detection module 220, a database server 230, a database 240, a
search engine 250, a sort module 260 and a notification module
270.
[0029] The user interface module 210 may present to the user 110
the user interface 130, on which the user 110 may search for an
object using reputation dimension 150 and related attributes 160 to
be used as part of a search criterion in searching for the object.
The user 110 may also select any of the reputation dimensions 150
presented in the user interface 130 to be applied in the search
criteria used to search for the object. The user 110 also has the
option of selecting any attribute 160 related to the selected
reputation dimension (s) 150 to be included in the search criteria
for the search.
[0030] The detection module 220 may detect the selected reputation
dimensions 150 and the selected related attributes 160 by the user
110. The search engine 250 may use the selected reputation
dimension(s) 150 and the attributes 160 detected by the detection
module 220, as part of the search query used to search the database
240 of objects via the database server 230.
[0031] In an example embodiment, the search engine 250 may use
other search criteria not shown in the user interface 130.
According to some example embodiments, the user 110 may require to
have the search result sorted, based on the selected reputation
dimensions 150 and the attributes 160 selected by the user 110. The
sort module 260 may sort the search results using the selected
reputation dimension(s) 150 (e.g., selected by the user 110 from a
list of reputation dimension 150 presented to the user.) The sort
module 260 may send the sorted results to the user interface module
210 for display to the user 110.
[0032] In an example embodiment, the notification module 270 may
provide a notification message to the user 110, in case where an
attribute 160 of a reputation dimension other than the reputation
dimensions 150 selected by the user transgresses a threshold (e.g.,
one of the feedback ratings or an overall feedback rating falls
below a predefined lower limit or exceeds a pre-defined higher
limit). The notification message provided by the notification
module 270 may be passed to the user interface module 210 to be
displayed in an appropriate location in the user interface 130
presented to the user 110.
[0033] FIG. 3 is a flow diagram illustrating an example embodiment
of a method 300 of searching for objects using reputation
information. The method 300 starts at operation 310, where the user
interface module 210 presents to the user 110, via a user interface
130, one or more reputation dimensions 150 and one or more
attributes 160 related to each of the reputation dimensions 150.
The user 110 then may select any of the reputation dimensions 150,
as well as the attributes 160 related to the selected reputation
dimension(s) 150, to be used in the search query when searching for
the object.
[0034] At operation 320, the detection module 220 may detect the
user 110 selection of the reputation dimensions 150 and attributes
160 related to the selected reputation dimension(s) 150. In an
example embodiment, at operation 330, the search engine 250 may
include the selected reputation dimension(s) 150 and selected
attribute(s) 160, related to the selected reputation dimension(s)
150, as a criterion part of a search query and conduct a search of
a database 240 of objects, using the database server 230, to
generate search results.
[0035] FIG. 4 is a flow diagram depicting an example embodiment of
a method 400 for sorting the search results of the method of FIG.
4. The method 400 starts at operation 410 where the sort module 260
checks the detected reputation dimension 150, selected by the user
110 and detected by the detection module 220, to determine if any
of the reputation dimensions 150 have been selected by the
user.
[0036] In control operation 420, it is determined whether the user
110 has selected at least one of the reputation dimensions 150 to
be included in the search query of the object. At operation 430,
the sort module 260 may sort the search results produced by the
search engine 250 according to the selected reputation dimension(s)
150 as shown in more detail in FIG. 7.
[0037] In an example embodiment, in a case where the user 110 did
not select any of the reputation dimensions presented via the user
interface 130, then the sort module 260 may sort the results
produced by the search engine 250, based on some default reputation
dimensions not selected by the user 110, or even not presented to
the user 110 via user interface 130.
[0038] At control operation 450, the notification module 270, may
determine that one or more reputation dimensions, associated with a
party other than the reputation dimension(s) 150 selected by the
user 110, have transgressed a threshold (e.g., one of the feedback
ratings or an overall feedback rating has fallen below a predefined
lower limit, or has exceeded a predefined higher limit). This
determination may be based on the information received from the
detection module 220 and the existing information stored on the
database 240. In that case, at operation 460, the notification
module 270 may provide a notification message via the user
interface module 210 to the user 110.
[0039] In an example embodiment, the user interface module 210 may
accordingly include the notification message in the user interface
130 in order to notify user 110. The notification message may be
displayed as a footnote or adjacent to the name of the party.
[0040] FIG. 5 is a diagram illustrating an example embodiment of
sets 500 of reputation dimensions 150 associated with sellers,
buyers, and service providers. The reputation information stored in
a database 240 may include feedback information related to sellers,
buyers, or service providers.
[0041] In some embodiments, the feedback information pertaining to
sellers may relate to one or more of the reputation dimensions 150
listed in box 510, including shipping and handling, listing
description, timeliness, and communication. The shipping and
handling reputation dimension, for example, may indicate that the
seller had negative feedback relating to some shipping and handling
aspects such as shipment timing, or quality of packaging. The
listing description aspect may correspond, for example, to a vague
description of a listed item or a description lacking some key
features of the listed items, etc.
[0042] An example list 520 presents some example reputation
dimensions pertaining to buyers that may have received feedback
from the sellers of the items. These reputation dimensions may be
related to timeliness in payment, communications, and returns.
Concerning the returns, the seller might have provided comments
regarding the quality of the packaging of a returned item or the
status of the returned item received from a buyer, compared to the
status of the item as it was delivered to the buyer.
[0043] In cases where some listed services are provided by some
service providers, a client may provide feedback related to the
reputation dimensions listed in box 530 including quality of the
service provided, cost of the service that was provided to the
client, timeliness of the provision of the services, and the
communication of the service provider with the client. In some
example embodiments, the client may be unsatisfied or very
satisfied with one or more aspects of a service received. The
client may also find some portions of the cost of service charged
by the service provider, excessive or irrelevant. The client may
include these observations in a feedback left for the service
provider.
[0044] FIG. 6 is a screenshot illustrating an example embodiment of
a user interface 600 including reputation dimensions added to the
search options. The user interface 600 may represent an example
user interface presented to the user 110 by the user interface
module 210. In the example user interface 600, the user 110 is
searching for an Apple iPod MP3 player. The user interface 600 may
include a search option box 610 and a list view portion 670.
[0045] The user 110 may select from the options provided in the
search option box 610 to limit his or her search to specific items.
The search engine 250 may use the selected options to find objects
of interest to the user 110. The user interface module 210 then may
present the results under the list view 670 of the user interface
600. In the example embodiment shown in FIG. 6, the list view 670
includes number of bids, price, and shipping cost.
[0046] The example search option box 610 may include a "show only"
portion 620. Only search objects satisfying the conditions listed
in the show only portion 620 may be listed under the list view 670.
The show only portion 620 of the search option box 610 in the
example user interface 600, includes a first reputation dimension
630 (R.D. 1) and a second reputation dimension 640 (R.D. 2)
[0047] Under the first reputation dimension 630 (e.g., shipping and
handling), a list box 650 may be included to show the selections of
attributes (e.g., feedback ratings such as 3, 4, 5, >3, etc.)
related to the first reputation dimension 630. The user 110 may
select, from the list box 650, the desired attributes of the first
reputation dimension 630 that he or she may desire to be included
in the search of the object. A list-box 660, shown under the second
reputation dimension 640 (e.g., negative feedback ratings), may
provide the user 110 with a list of attributes (e.g., <20%,
<10%, <5%, etc.) related to the second reputation dimension
640 that the user may select from. The selection of first and
second reputation dimensions 630 and 640 may affect the search
results generated by the search engine 250 as shown in FIG. 7.
[0048] FIG. 7 is a screenshot illustrating an example embodiment of
a user interface 700, including reputation dimensions in the search
options and displaying search results sorted based on selected
reputation dimensions. According to the example user interface 700,
the user 110 has selected both the first and the second reputation
dimensions 630 and 640 to be included as the search criteria for an
Apple iPod.
[0049] The selections of the first reputation dimension 630 and the
second reputation dimension 640 are reflected in the search results
by including R.D. 1 and R.D. 2 as columns 720 and 740 of the list
view 670. According to the example user interface 700, the user 110
has selected the shown attribute of greater than 3 (>3) from the
list-box 650 as a selected attribute of the selected first
reputation dimension 630. Also, by selecting the second reputation
dimension 640 and the attribute value of less than 5 percent from
the list-box 660, the user 110 may have requested that only the
Apple iPods having the qualifications corresponding to the
selections be shown in the search result.
[0050] Accordingly, only two of the Apple iPods presented in FIG. 6
have been selected to be included in the listed view of the user
interface 700. For both of the included Apple iPods, the value of
the first reputation dimension 630 in column 720 is higher than 3
(e.g., 4 and 5); and both of these iPods are showing values of the
second reputation dimension 640 (column 740) less than 5% (e.g., 4%
and 1%). In some example embodiments, the first and the second
reputation dimensions 630 and 640 may include any of the reputation
dimensions listed in FIG. 5 (e.g., shipping and handling, listing
description, timeliness, communications, etc.).
[0051] FIG. 8 is a high-level block diagram illustrating an example
embodiment of a network-based publication system 800, having a
client-server architecture for performing search using multifaceted
reputation information. A publication platform, in the example form
of a network-based marketplace 802, provides server-side
functionality, via a network 180 (e.g., the Internet) to one or
more clients. FIG. 8 illustrates, for example, a web client 806
(e.g., a browser, such as the INTERNET EXPLORER browser developed
by MICROSOFT CORPORATION of Redmond, Wash.), and a programmatic
client 808 executing on respective client machines 810 and 812.
[0052] Turning specifically to the network-based marketplace 802,
an Application Program Interface (API) server 814 and a web server
816 are coupled to, and provide programmatic and web interfaces
respectively to, one or more application servers 818. The
application servers 818 host one or more marketplace applications
820 and multifaceted search applications 822. The application
servers 818 are, in turn, shown to be coupled to one or more
database servers 824 that facilitate access to one or more
databases 826.
[0053] The marketplace applications 820 provide a number of
marketplace functions and services to users that access the
marketplace 802. The multifaceted search applications 822
facilitates online search for objects using reputation dimensions
as part of the search query.
[0054] Further, while the system 800 shown in FIG. 8 employs a
client-server architecture, the present application is of course
not limited to such an architecture, and could equally well find
application in a distributed, or peer-to-peer, architecture system.
The various marketplace and multifaceted search applications 820
and 822 may also be implemented as standalone software programs,
which do not necessarily have networking capabilities.
[0055] The web client 806, it will be appreciated, may access the
various marketplace and multifaceted search applications 820 and
822 via the web interface supported by the web server 816.
Similarly, the programmatic client 808 accesses the various
services and functions provided by the marketplace and multifaceted
search applications 820 and 822 via the programmatic interface
provided by the API server 814. The programmatic client 808 may,
for example, be a seller application (e.g., the TurboLister
application developed by EBAY INC., of San Jose, Calif.) to enable
sellers to author and manage listings on the marketplace 802 in an
off-line manner, and to perform batch-mode communications between
the programmatic client 808 and the network-based marketplace
802.
[0056] FIG. 8 also illustrates a third party application 828,
executing on a third party server machine 830, as having
programmatic access to the network-based marketplace 802 via the
programmatic interface provided by the API server 814. For example,
the third party application 828 may, utilizing information
retrieved from the network-based marketplace 802, support one or
more features or functions on a website hosted by the third party.
The third party website may, for example, provide one or more
promotional, marketplace or payment functions that are supported by
the relevant applications of the network-based marketplace 802.
[0057] FIG. 9 is a diagram illustrating multiple example
marketplace and multifaceted search applications 900 that, in one
example embodiment, are provided as part of the network-based
marketplace 802. The marketplace 802 may provide a number of
listing and price-setting mechanisms whereby a seller may list
goods or services for sale, a buyer may express interest in or
indicate a desire to purchase such goods or services, and a price
may be set for a transaction pertaining to the goods or
services.
[0058] The marketplace applications 820 are shown to include one or
more auction applications 902 which support auction-format listing
and price setting mechanisms (e.g., English, Dutch, Vickrey,
Chinese, Double, Reverse auctions etc.). The various auction
applications 902 may also provide a number of features in support
of such auction-format listings, such as a reserve price feature
whereby a seller may specify a reserve price in connection with a
listing and a proxy-bidding feature whereby a bidder may invoke
automated proxy bidding.
[0059] A number of fixed-price applications 904 support fixed-price
listing formats (e.g., the traditional classified
advertisement-type listing or a catalogue listing) and buyout-type
listings. Specifically, buyout-type listings (e.g., including the
Buy-It-Now (BIN) technology developed by eBay Inc., of San Jose,
Calif.) may be offered in conjunction with an auction-format
listing, and allow a buyer to purchase goods or services, which are
also being offered for sale via an auction, for a fixed-price that
is typically higher than the starting price of the auction.
[0060] Reputation applications 906 may allow parties that transact
utilizing the network-based marketplace 802 to establish, build,
and maintain reputations related to market participants (e.g.,
sellers, buyers, service providers, or clients) which may be
published and made available to potential trading partners.
Consider that where, for example, the network-based marketplace 802
supports person-to-person trading, users may have no history or
other reference information whereby the trustworthiness and
credibility of potential trading partners may be assessed. The
reputation applications 906 may allow a user, for example through
feedback provided by other transaction partners, to establish a
reputation within the network-based marketplace 802 over time.
Other potential trading partners may then reference such a
reputation for the purposes of assessing credibility and
trustworthiness.
[0061] Listing creation applications 910 may allow sellers or
service providers to conveniently author listings pertaining to
goods or services that they wish to sell via the marketplace
802.
[0062] Dispute resolution applications 914 may provide mechanisms
whereby disputes arising between transacting parties may be
resolved. For example, the dispute resolution applications 914 may
provide guided procedures whereby the parties are guided through a
number of steps in an attempt to settle a dispute. In the event
that the dispute cannot be settled via the guided procedures, the
dispute may be escalated to a third party mediator or
arbitrator.
[0063] Feedback analysis applications 912 may allow the
network-based marketplace 802 to analyze feedback information
received by the reputation applications 906 and make assessments
with respect to performances of the trading parties. The feedback
analysis applications 912 may provide attributes (e.g., rankings,
percentages, comments, etc.) related to reputation dimensions
(e.g., overall feedback rating, feedback ratings on cost of
shipping, timeliness, communication, quality of advertisements,
quality of listing descriptions, quality of packaging, quality of
services provided, and the like). These attributes may be used by
sorting applications 916 to sort search results generated by search
applications 922.
[0064] As part of the multifaceted search applications 822, search
applications 922 may facilitate searching objects using reputation
dimensions from reputation applications 906 and attributes related
to the reputation dimensions provided by the feedback analysis
applications 912, as part of their search query. The search results
may be provided to sorting applications 916 for sorting.
[0065] The sorting applications 916 may obtain the search results
provided by the search applications 922 and sort the results based
on the selected attributes related to reputation dimensions of
interest to the user. For example a user may desire to sort found
objects based on feedback ratings on timeliness of sellers of found
objects. For example, the user may select that only objects offered
by sellers who have timeliness rating score higher than 6 be
displayed. The sorting applications 916, then may sort the search
results according to the seller's timeliness ranting score and only
list those objects for which the sellers have timeliness scores
better than 6. The sorting applications 916 may then send the
listed objects to user interface applications 924 to be displayed
to the user.
[0066] Messaging applications 920 are responsible for the
generation and delivery of messages to users of the network-based
marketplace 802. Such messages may, for example, advise users
regarding the status of listings at the network-based marketplace
802 (e.g., providing "outbid" notices to bidders during an auction
process or providing promotional and merchandising information to
users). In one example embodiment, the messaging applications 920
may notify a user, when an entity (e.g., seller, buyer, service
provider, or client) associated with a searched object has
transgressed a predefined threshold related to an attribute of a
reputation dimension other than the ones selected by the user as a
search query (e.g., the user has selected the shipping cost as the
search criteria but among the found objects, there are ones offered
by sellers who have more than 35% late delivery of sold items. In
this case, the messaging applications may notify the user of such
instances if the predefined threshold is 20%)
Example Machine Architecture
[0067] FIG. 10 is a block diagram, illustrating a diagrammatic
representation of machine 1000 in the example form of a computer
system within which a set of instructions for causing the machine
to perform any one or more of the methodologies discussed herein
may be executed. In alternative embodiments, the machine 1000 may
operate as a standalone device or may be connected (e.g.,
networked) to other machines. In a networked deployment, the
machine 1000 may operate in the capacity of a server or a client
machine in a server-client network environment, or as a peer
machine in a peer-to-peer (or distributed) network environment. The
machine 1000 may be a server computer, a client computer, a
personal computer (PC), a tablet PC, a set-top box (STB), a
Personal Digital Assistant (PDA), a cellular telephone, a web
appliance, a network router, switch or bridge, or any machine
capable of executing a set of instructions (sequential or
otherwise) that specify actions to be taken by that machine.
Further, while only a single machine is illustrated, the term
"machine" shall also be taken to include any collection of machines
that individually or jointly execute a set (or multiple sets) of
instructions to perform any one or more of the methodologies
discussed herein.
[0068] The example computer system 1000 may include a processor
1060 (e.g., a central processing unit (CPU), a graphics processing
unit (GPU) or both), a main memory 1070 and a static memory 1080,
all of which communicate with each other via a bus 1008. The
computer system 1000 may further include a video display unit 1010
(e.g., liquid crystal displays (LCD) or cathode ray tube (CRT)).
The computer system 1000 also may include an alphanumeric input
device 1020 (e.g., a keyboard), a cursor control device 1030 (e.g.,
a mouse), a disk drive unit 1040, a signal generation device 1050
(e.g., a speaker) and a network interface device 1090.
[0069] The disk drive unit 1040 may include a machine-readable
medium 1022 on which is stored one or more sets of instructions
(e.g., software 1024) embodying any one or more of the
methodologies or functions described herein. The software 1024 may
also reside, completely or at least partially, within the main
memory 1070 and/or within the processor 1060 during execution
thereof by the computer system 1000, the main memory 1070 and the
processor 1060 also constituting machine-readable media.
[0070] The software 1024 may further be transmitted or received
over a network 280 via the network interface device 1090.
[0071] While the machine-readable medium 1022 is shown in an
example embodiment to be a single medium, the term
"machine-readable medium" should be taken to include a single
medium or multiple media (e.g., a centralized or distributed
database, and/or associated caches and servers) that store the one
or more sets of instructions. The term "machine-readable medium"
shall also be taken to include any medium that is capable of
storing, encoding or carrying a set of instructions for execution
by the machine and that cause the machine to perform any one or
more of the methodologies of the present invention. The term
"machine-readable medium" shall accordingly be taken to include,
but not be limited to, solid-state memories and optical and
magnetic media.
[0072] Thus, a method and a system for searching for objects using
reputation dimensions and their attributes as part of search query
have been described. Although the present invention has been
described with reference to specific example embodiments, it will
be evident that various modifications and changes may be made to
these embodiments without departing from the broader spirit and
scope of the invention. Accordingly, the specification and drawings
are to be regarded in an illustrative rather than a restrictive
sense.
[0073] The Abstract of the Disclosure is provided to comply with 37
C.F.R. .sctn.1.72(b), requiring an abstract that will allow the
reader to quickly ascertain the nature of the technical disclosure.
It is submitted with the understanding that it will not be used to
interpret or limit the scope or meaning of the claims. In addition,
in the foregoing Detailed Description, it may be seen that various
features are grouped together in a single embodiment for the
purpose of streamlining the disclosure. This method of disclosure
is not to be interpreted as reflecting an intention that the
claimed embodiments require more features than are expressly
recited in each claim. Rather, as the following claims reflect,
inventive subject matter lies in less than all features of a single
disclosed embodiment. Thus the following claims are hereby
incorporated into the Detailed Description, with each claim
standing on its own as a separate embodiment.
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