U.S. patent application number 13/270011 was filed with the patent office on 2012-02-02 for matching social network users.
This patent application is currently assigned to MeetMyKind LLC. Invention is credited to Melissa Leonard.
Application Number | 20120030287 13/270011 |
Document ID | / |
Family ID | 42172821 |
Filed Date | 2012-02-02 |
United States Patent
Application |
20120030287 |
Kind Code |
A1 |
Leonard; Melissa |
February 2, 2012 |
Matching Social Network Users
Abstract
Systems and methods are disclosed for matching of individuals to
one another using a matching model. The matching model matches
social network users based on ratings given by users one to
another, as well as, as appropriate and available, explicit
attributes indicated by users and other data such as location data
and system usage data.
Inventors: |
Leonard; Melissa; (Woodland
Hills, CA) |
Assignee: |
MeetMyKind LLC
Woodland Hills
CA
|
Family ID: |
42172821 |
Appl. No.: |
13/270011 |
Filed: |
October 10, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12622729 |
Nov 20, 2009 |
8060573 |
|
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13270011 |
|
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61116304 |
Nov 20, 2008 |
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Current U.S.
Class: |
709/204 |
Current CPC
Class: |
G06Q 10/10 20130101 |
Class at
Publication: |
709/204 |
International
Class: |
G06F 15/16 20060101
G06F015/16 |
Claims
1. A process for recommending prospects to social network users,
the process comprising: obtaining personal attribute information
from a first plurality of the users; obtaining desired-prospect
attribute information from a second plurality of the users;
recommending prospects to a third plurality of the users, wherein
the recommended prospects have acceptable proximities to the third
plurality of users based upon ratings, the desired-prospect
attribute information and the personal attribute information,
wherein the ratings reflect a quality of match.
2. The process of claim 1 further comprising obtaining the ratings
from a fourth plurality of the users.
3. The process of claim 1 further comprising obtaining the ratings
by estimating which users are most like other users based on users
having similar ratings of other users.
4. The process of claim 1 wherein at least some of the users are
also prospects, the process further comprising identifying users
that have rated each other high and low, and using these
identifications in conjunction with an estimate of how similar one
user is to the other to derive ratings as estimates of how the
users will rate other users that they have not yet rated.
5. The process of claim 1 wherein recommending comprises scoring
user-prospect matches to indicate quality of match between
respective prospects and users, wherein the scores are derived from
weighting plural matched attribute information of the prospects to
the users' desired-prospect attributes.
6. The process of claim 1 further comprising providing to a fifth
plurality of the users respective preliminary lists of prospects,
and obtaining from the fifth plurality of users each user's rating
of the prospects in the user's respective preliminary list, wherein
the ratings reflect the user's opinion of a quality of match of the
prospects in the preliminary list, wherein the fifth plurality of
the users comprises a subset of the first plurality of users, the
second plurality of users and the third plurality of the users.
7. The process of claim 1 wherein if a prospect is deemed to be a
potential match for a given user based on a combination of
proximity data and other data, then evaluating whether the
prospect's attributes match the user's desired-attributes.
8. The process of claim 1 wherein recommending further comprises
categorizing the prospects.
9. The process of claim 8 wherein the categories are selected from
the group consisting of dating, friendship, activities, networking,
deal making and reuniting.
10. The process of claim 1 wherein at least some of the users rate
other users.
11. The process of claim 1 wherein recommending further comprises
scoring matches of users and prospects.
12. The process of claim 11 further comprising adjusting the scores
based on the attributes of the prospect being rated.
13. The process of claim 11 further comprising adjusting the scores
based on the ratings.
14. The process of claim 1 further comprising invalidating ratings
by a given user if the given user has a pattern of ratings which
fail to correlate to ratings by other users.
15. Apparatus comprising a machine readable storage medium storing
a program having instructions which when executed by a processor
will cause the processor to recommend prospects to social network
users, the instructions of the program for: obtaining personal
attribute information from a first plurality of the users;
obtaining desired-prospect attribute information from a second
plurality of the users; recommending prospects to a third plurality
of the users, wherein the recommended prospects have acceptable
proximities to the third plurality of users based upon ratings, the
desired-prospect attribute information and the personal attribute
information, wherein the ratings reflect a quality of match.
16. The apparatus of claim 15, the instructions of the program
further for obtaining the ratings from a fourth plurality of the
users.
17. The apparatus of claim 15, the instructions of the program
further for obtaining the ratings by estimating which users are
most like other users based on users having similar ratings of
other users.
18. The apparatus of claim 15 wherein at least some of the users
are also prospects, the instructions of the program further for
identifying users that have rated each other high and low, and
using these identifications in conjunction with an estimate of how
similar one user is to the other to derive ratings as estimates of
how the users will rate other users that they have not yet
rated.
19. The apparatus of claim 15 wherein recommending comprises
scoring user-prospect matches to indicate quality of match between
respective prospects and users, wherein the scores are derived from
weighting plural matched attribute information of the prospects to
the users' desired-prospect attributes.
20. The apparatus of claim 15, the instructions of the program
further for providing to a fifth plurality of the users respective
preliminary lists of prospects, and obtaining from the fifth
plurality of users each user's rating of the prospects in the
user's respective preliminary list, wherein the ratings reflect the
user's opinion of a quality of match of the prospects in the
preliminary list, wherein the fifth plurality of the users
comprises a subset of the first plurality of users, the second
plurality of users and the third plurality of the users.
21. The apparatus of claim 15, the instructions of the program
further for, if a prospect is deemed to be a potential match for a
given user based on a combination of proximity data and other data,
then evaluating whether the prospect's attributes match the user's
desired-attributes.
22. The apparatus of claim 15 wherein recommending further
comprises categorizing the prospects.
23. The apparatus of claim 22 wherein the categories are selected
from the group consisting of dating, friendship, activities,
networking, deal making and reuniting.
24. The apparatus of claim 15 wherein at least some of the users
rate other users.
25. The apparatus of claim 15 wherein recommending further
comprises scoring matches of users and prospects.
26. The apparatus of claim 15, the instructions of the program
further for adjusting the scores based on the attributes of the
prospect being rated.
27. The apparatus of claim 26, the instructions of the program
further for adjusting the scores based on the ratings.
28. The apparatus of claim 15, the instructions of the program
further for invalidating ratings by a given user if the given user
has a pattern of ratings which fail to correlate to ratings by
other users.
29. The apparatus of claim 15 further comprising a user input
device, a display device, and a processor.
Description
RELATED APPLICATION INFORMATION
[0001] This application is a continuation of application Ser. No.
12/622,729 which was filed Nov. 20, 2009, and is titled "Matching
Social Network Users", which claims priority from provisional
Application No. 61/116,304 filed Nov. 20, 2008 and entitled "System
and Method for Matching Social Network Users" which is incorporated
herein by reference.
NOTICE OF COPYRIGHTS AND TRADE DRESS
[0002] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. This patent
document may show and/or describe matter which is or may become
trade dress of the owner. The copyright and trade dress owner has
no objection to the facsimile reproduction by anyone of the patent
disclosure as it appears in the Patent and Trademark Office patent
files or records, but otherwise reserves all copyright and trade
dress rights whatsoever.
BACKGROUND
[0003] 1. Field
[0004] This disclosure relates to matching of individuals one to
another through online systems or through use of mobile, wireless,
and/or electronic devices.
[0005] 2. Description of the Related Art
[0006] Social network services have been in existence for a number
of years. Social network services typically consist of online
communities of individuals who share common background, attributes,
interests and/or activities, and who are interested in meeting
and/or interacting with other individuals in the network. Most
social network services are web based and provide a variety of ways
for users to interact, such as e-mail, instant messaging, posting
blogs, and posting comments on each other's social network profile
pages. A number of social network services have developed solutions
to accommodate users participating in social networks through use
of wireless devices, and other portable electronic devices.
[0007] Conventional social networking solutions, such as online
social networks, typically require a user who wants to find other
members that share similar interests to designate the specific
attributes sought at the same time as the user wants to find these
members. It is often difficult to find users with desired qualities
because conventional social networking solutions typically have
many users, and entering desired attributes often returns too many
potential matches. Searching for other members that a user would
find of interest oftentimes requires sorting through the profiles
and data of many other members and/or performing multiple searches
to find individuals of interest.
[0008] Users of many conventional social networks may also search
for individuals that one may have interest in by scanning though
the profiles and data of users associated with already-known
members. In some instances, meeting individuals who have an
established relationship with an already-known individual may
require a user to request permission from a user's already-known
contact, the person of interest, or both. This results in a delay
for the user before the user can meet the person of interest as
well as additional user effort.
[0009] Further, although a user may find another member in a social
network desirable and may want to interact with that individual, it
is often difficult to determine if the user himself or herself has
attributes that the other individual would find desirable.
DESCRIPTION OF THE DRAWINGS
[0010] FIG. 1 is a first flowchart of a process for matching social
network users.
[0011] FIG. 2 is a second flowchart of a process for matching
social network users.
[0012] FIG. 3 is a screen display of a registration interface.
[0013] FIG. 4 is a screen display of an attribute definition
interface.
[0014] FIG. 5 is a screen display displaying potential matches.
[0015] FIG. 6 is a screen display of a profile and rating
interface.
[0016] FIG. 7 is a screen display of an email message creation
interface.
[0017] FIG. 8 is a system block diagram of a system for matching
social network users.
DETAILED DESCRIPTION
[0018] Systems and methods for recommending matches of people in
social networks are described. The systems and methods provide a
registered user of a social network system (a user) with a
mechanism for locating and interacting with other people that may
or may not be registered users of the social network system
(prospects). A user may find prospects by entering explicit
attributes that the user is looking for in prospects, through the
user's ratings of other users (e.g., prospects), and through other
data such as data gathered about the user's interaction with other
users. This may go beyond the explicit attributes that a user would
want a prospect to have to infer the prospects that a user would
have interest in based on the ratings the user has entered about
other users, the user's interaction with the system, and other
data.
[0019] The process for a user to find prospects of interest may
initiate with a user registering with an online system. For
example, the user may be asked to enter basic identifying
information into the system, and may be prompted to enter further
information (e.g., profile information) about the user as the user
would like. A user may create a user profile. A user may attach
files such as one or more digital photograph files to their
profile. The user may also be prompted to enter the attributes that
the user would want to find in matched prospects.
[0020] Explicit attribute data and rating data may be entered by
the user and used to find prospects of interest. The system may use
a model to determine the similarity of one user to another user
based on scores that the system maintains about the characteristics
of each user (e.g., attribute scores) and scores that represent the
type of prospects that a user would want to meet (e.g., matching
scores). For example, a user may enter data about the user stating
that the user is funny and good-looking. The system, in this
example, would capture a high score for the "funny" attribute
category and a high score for a "physical attractiveness" attribute
category. As an extension of the present example, the user may
enter attributes regarding the prospects that the user would want
to meet. For example, the user may enter that the user would be
interested to meet "funny" and "physically attractive" users, and
the matching scores for these two categories would resultantly be
high.
[0021] According to the model, a variance (e.g., proximity) between
the attribute scores of a user and the matching scores of
prospects, and the matching scores of a user and the attribute
scores of prospects may be obtained. As the attributes scores
indicate the attributes that a user possesses, and the matching
scores indicate the attributes that a user is seeking, by
calculating the variance between the user's matching and the
prospect's attribute scores, and the prospect's matching scores and
the user's attribute scores, a nearest-to match can be derived.
This type of matching is referred to as attribute and matching
score proximity matching, herein. Look-up tables may be used
instead of or in addition to calculations.
[0022] Further, the system may use the rating scores of users and
prospects to validate and adjust the attribute scores and matching
scores of the users and the prospects. As an extension of the prior
example, if collected data indicates that a user likes funny
individuals and the user rates a prospect low, the system may infer
that the prospect is not funny.
[0023] Some prospects may have similar ratings to other prospects.
These similarities may be used to indicate prospects which are
similar one to another and a degree of similarity. A user may be
matched with prospects that are most-like those the user has rated
higher in the past, where the prospects have, in turn, rated users
similar to the user higher in the past. This type of matching is
referred to as rating score proximity matching.
[0024] Attribute and matching score proximity data and rating score
proximity data may be combined with explicit attribute data and
other data to recommend prospect matches for the user. A relevance
engine may be used in the matching process.
[0025] A user may view stored information about prospects and
interact with prospects. If a user is interested in contacting or
learning more about a recommended (e.g., matched) prospect, the
user may view the profile and other information entered by the
prospect. Once a related button or link is selected, a document
(e.g., a web page or voice message) may be presented to the user
that comprises more detailed profile information and/or other
information about the prospect. The user can also initiate
communication with the user. If the user wishes to communicate with
the prospect, the user can elect to send a message to the user. For
example, the user may select a command button or link that causes
the system to transmit a response message to the user via a
computer network.
[0026] A user may rate a prospect by selecting a button that
indicates how good of a match the prospect is for the user. A
prospect may be able to rate a user by selecting a button that
indicates how good of a match the user is for the prospect.
Following, these ratings may be used by the matching model to
further refine the matches that are offered to each user.
[0027] The Overall Matching Process:
[0028] Referring now to FIG. 1 there is shown a flow chart of a
process for locating prospects that may be of interest to a user.
FIG. 1 illustrates how a user may interact with prospects and for
users and prospects to rate (e.g., provide a rating for) one
another. FIG. 1 illustrates how to refine what is known about each
user and subsequent matching based on the ratings given by one user
to the next.
[0029] The Registration Process:
[0030] The process may initiate at 100 when the user (e.g., a user
wishing to locate and/or interact with one or more persons of
interest), registers with the system. The user enters information
about the client user at 101. Various kinds of information may be
obtained from the user. The system may, for example, provide the
user with an interface for entering a user name, a password, and
other information associated with the user in order to identify the
user.
[0031] Users may enter information about themselves through a
registration interface such as that shown in FIG. 3. Such
information may comprise a user's gender 132, birth date 133,
relationship status 134, height in feet 135 and inches 136, zip
code 137, body type 138, and other profile information. Profile
information may comprise any type of information that would help
define and/or explain the user's character traits, personality
physical attributes and/or other personal attributes.
[0032] Referring again to FIG. 1, the information entered by a user
at 101 (e.g., through a registration interface illustrated in FIG.
3) is then stored for later retrieval at 102.
[0033] Sought Attributes Entry Process:
[0034] As shown at 115 and 103, users may be given an opportunity
to enter the explicit attributes that users want to find in
prospects. Users may specify that they want to be matched for
dating, for friendship, for networking and many other reasons.
Users may enter sought attributes for each of these relationship
categories.
[0035] Referring now to FIG. 4, a sought attributes interface
presented to the user is shown. The sought attributes interface
presents each user with the ability to enter information regarding
the attributes that the user would like matched prospects to
possess. Such information may comprise a user's gender 143, age
144, height 145, relationship status 146, and other factors.
[0036] Referring again to FIG. 1, the information entered at 103
(e.g., through the sought attributes definition interface as
illustrated in FIG. 4) is then stored for later retrieval at
104.
[0037] Matching Prospects to Users:
[0038] As shown at 116 and 105 in FIG. 1, the system may match
prospects to a user by use of a matching model. Explicit attributes
entered by the user at 103 may be used for matching. Rating and
other data may be used for matching insofar as the relevant data is
available for a user.
[0039] Referring now to FIG. 2 there is shown a process for
utilising rating data entered by users to determine optimal matches
of users to prospects. Further, FIG. 2 illustrates how a user may
find prospects that have only those attributes that are explicitly
entered by a user (e.g., through a sought attributes definition
interface as illustrated in FIG. 4, and as provided in step 103 in
FIG. 1). Further, FIG. 2 illustrates how to refine what is known
about what each user and about what each user is seeking in
potential prospects, thereby improving subsequent matching based on
the ratings given by one user to the next.
[0040] The matching model process initiates at 118 and 119 when the
system calculates the proximity of users and prospects utilizing
rating data at 120 (e.g., as collected, for example, at 195 in an
example interface illustrated in FIG. 6). Further, the system may
utilize rating data to estimate which users are most like other
users based on users receiving similar ratings from other users
(e.g., where two users obtain high ratings from the same
individual, this would serve to identify that these users are more
similar than where two users have obtained different ratings).
Further, the system may identify users that have rated each other
high and low, and utilize this data in conjunction with the
estimate of how similar one user is to the next to estimate how
users will rate other users that they have not yet rated.
[0041] Matching and attribute scores may be used at 122 to estimate
the proximity of users to prospects at 121 (e.g., the system uses
matching scores, that represent estimated levels of certain
attributes that individual users are seeking and attribute scores,
that represent the estimated attributes that individual users
possess, to determine optimal matches). The matches for users may
be determined by calculating the distance between a user's matching
scores and a prospect's attribute scores, and the distance between
a prospect's matching scores and a user's attribute scores.
[0042] The matches for users may be determined through
incorporating other data at 124 such as the geographic distance
between users and prospects. The proximity data calculated in steps
119 and 121, and other data at 124 may be used to determine
potential matches for the client user. If the prospect is not a
match for the user at 125, the system may reject the prospect as a
match for the user at 126. On the other hand, if the prospect is
deemed to be a potential match for the user based on the
combination of proximity data and other data at 123 and 125, the
system may evaluate whether the prospect's attributes match the
attributes explicitly entered by the user at 128.
[0043] Steps 119, 121, and 123 may each be executed insofar as
relevant data is available for the user being matched.
[0044] If the prospect's attributes don't match the desired
attributes explicitly entered by the user, the prospect is rejected
as a match for the client user at 126. If the prospect's attributes
match what has been entered by the user as desired, the system
evaluates whether the prospect user has been blocked by the user at
129. If the prospect has been blocked by the user, the prospect is
rejected as a match for the prospect user at 126. If the prospect
user has not been blocked by the user, a determination is made
regarding whether to display the prospect as a match for the user
at 130. For example, a prospect may not be displayed as a match for
a user if the user has formerly met and rated the prospect (see
FIG. 6, step 195). Additionally, for example, a prospect may not be
displayed as a match for the user if the user has already added the
prospect as a friend (see FIG. 6, step 201) or if the user has
explicitly indicated that the user would want to remove the
prospect as a match (see FIG. 6, step 202). If the prospect is to
be displayed as a match for the user, the prospect's profile
information may be displayed or otherwise made available to the
user, as appropriate, at 131.
[0045] Displaying Matched Prospects to Users:
[0046] Referring again to FIG. 1, at step 105 matched prospects are
displayed to users based on whether the system determines whether
each matched prospect should be displayed (see FIG. 2 step
131).
[0047] Referring now to FIG. 5, a screen display of a matched
prospects interface presented to the user is shown. A user may be
presented with matched prospects in various categories such as
matches for dating at 155, matches for friendship at 161, matches
for activities at 168, matches for networking at 173, matches for
deal making at 181, and matches for reuniting at 187. Other and/or
different relationship categories may be displayed in the prospects
interface.
[0048] For each relationship category shown in the prospect
interface, the top user profiles may be presented to users. For
example, in the contemplated "Dating" relationship section shown at
155, the top matches are shown at 156, 157, and 159. Further,
additional matches may be referenced as seen at 158. Specific
explicit attribute filters may be set for each type of
relationship, for example, at 154, 160, 166, 176, 182, and 188.
These explicit attribute filters may be used to determine what
matches are presented to users, as referenced at 128 in FIG. 2.
[0049] Displaying Profile Information of Matched Prospects to
Users:
[0050] Users may view profiles of other users. FIG. 6 presents an
example view of a profile display interface. Users may navigate to
such profile interface by clicking on the photo of a prospect (for
example, at 156) in the matched prospect interface in FIG. 5. Links
on the profile display interface may allow users to indicate how
the user wishes to interact with other users or manage the
relationship with other users. For instance, links may allow the
user to open an email interface at 197 (see FIG. 7), view a
prospect's profiles on other social networking sites at 198,
navigate to see the friends interface at 199, send "wink" messages
to other users at 200, invite other users as friends at 201, remove
one or more users as prospect matches at 202, block prospects from
contacting the users at 203, and see the blogs of the prospect at
204. Further, users may rate prospects when accessing the
prospects' profile at 194 and 195.
[0051] Interaction Between Prospects and Users:
[0052] Users may send email to prospects such as by clicking on a
link on the profile interface at 197. Clicking on a certain link on
profile interface at 197 will cause an email interface such as
shown in FIG. 7 to display to the user.
[0053] Referring now to FIG. 7, an example of the email interface
presented to the user is shown. Users will be, for example, able to
enter a message to a prospect (for example, at 216) in the matched
prospect interface in FIG. 5. Users may be provided with text
formatting tools 206, such as tools to bold text 207, to underline
text 209, to bullet text 211, to change the font type 213, to
change font size 214, and/or to change font color 215. Further,
users may be able to enter a subject line for their messages
205.
[0054] Computer Execution Environment (Hardware):
[0055] The systems and methods disclosed herein may be implemented
as computer software in the form of computer readable program code
executed on one or more general-purpose computers or other
computing device and through a communication network such as the
system illustrated in FIG. 8. The system consists of servers such
as one or more web servers 231, one or more application servers
232, one or more database servers 233, and/or one or more email
servers 234. Users may be able to access the computer system via
computer 221 and via cell phone or mobile device 235. For example,
if users access the system via computer 221, the computer would
access the system through the Internet 222. The system may
incorporate routing and switching 223, 224, 225, and 226, and one
or more load balancers 227 and 228 to appropriately route Internet
traffic to the appropriate hardware (such as servers). The system
may incorporate one or more computer firewalls 229 and 230 to help
ensure only permitted traffic is allowed to system hardware. The
system may be deployed in cloud architecture.
[0056] Access may be provided to users through a telephone/wireless
network as illustrated in steps 239, 238, 237, 236 and 235 in FIG.
8. Such telephone/wireless access, for example, will allow users to
receive voice and/or portable computer access to system
functionality
[0057] As shown, prospects may be recommended to the user based in
whole or in part on the ratings the user has given previous matches
(e.g., in addition to sought attributes explicitly entered by the
user), functionality to utilize the rating information entered by
users to further refine what is known about users and users'
preferences, and ability to have prospects recommended to the user
utilizing this refined understanding of each user and each user's
preferences. Collectively or in part, this may allow users to have
matches provided to them and matches further refined as they
continue to use the system. Further, information entered by users
may be validated through refinement provided via the ratings given
by other users. Further, users may obtain an understanding of the
prospects that the user would find desirable further refined as the
user uses the system.
[0058] Further, matches may be provided to the users based on
attributes that may not be explicitly captured in the system. The
system may match users to prospects based on attributes not
explicitly captured in the system since prospects may be
recommended to the user based on the collective ratings provided to
the prospect, and the commonality which has caused the prospect to
be rated similarly by others may not be explicitly captured as an
attribute in the system.
[0059] The matching model matches each user to those that are
estimated to have similar and/or dissimilar characteristics to
those that the user has previously indicated higher or lower
preference for. Rating data may be used to refine what is
understood about users and/or user matching preferences. This data
may be used in matching users one to another.
[0060] A client computer may include software and/or hardware for
providing functionality and features described herein. A client
computer may therefore include one or more of: logic arrays,
memories, analog circuits, digital circuits, software, firmware,
and processors such as microprocessors, field programmable gate
arrays (FPGAs), application specific integrated circuits (ASICs),
programmable logic devices (PLDs) and programmable logic arrays
(PLAs). The hardware and firmware components of the client computer
100 may include various specialized units, circuits, software and
interfaces for providing the functionality and features described
here. The processes, functionality and features may be embodied in
whole or in part in software which operates on a client computer
and may be in the form of firmware, an application program, an
applet (e.g., a Java applet), a browser plug-in, a COM object, a
dynamic linked library (DLL), a script, one or more subroutines, or
an operating system component or service. The hardware and software
and their functions may be distributed such that some components
are performed by a client computer and others by other devices.
[0061] Although shown implemented in a personal computer, the
processes and apparatus may be implemented with any computing
device. A computing device as used herein refers to any device with
a processor, memory and a storage device that may execute
instructions including, but not limited to, personal computers,
server computers, computing tablets, set top boxes, video game
systems, personal video recorders, telephones, smart phones,
portable computers, and laptop computers. These computing devices
may run an operating system, including, for example, variations of
the Linux, Microsoft Windows, and Apple Mac operating systems.
[0062] Closing Comments
[0063] Throughout this description, the embodiments and examples
shown should be considered as exemplars, rather than limitations on
the apparatus and procedures disclosed or claimed. Although many of
the examples presented herein involve specific combinations of
method acts or system elements, it should be understood that those
acts and those elements may be combined in other ways to accomplish
the same objectives. With regard to flowcharts, additional and
fewer steps may be taken, and the steps as shown may be combined or
further refined to achieve the methods described herein. Acts,
elements and features discussed only in connection with one
embodiment are not intended to be excluded from a similar role in
other embodiments.
[0064] As used herein, "plurality" means two or more. As used
herein, a "set" of items may include one or more of such items. As
used herein, whether in the written description or the claims, the
terms "comprising", "including", "carrying", "having",
"containing", "involving", and the like are to be understood to be
open-ended, i.e., to mean including but not limited to. Only the
transitional phrases "consisting of" and "consisting essentially
of", respectively, are closed or semi-closed transitional phrases
with respect to claims. Use of ordinal terms such as "first",
"second", "third", etc., in the claims to modify a claim element
does not by itself connote any priority, precedence, or order of
one claim element over another or the temporal order in which acts
of a method are performed, but are used merely as labels to
distinguish one claim element having a certain name from another
element having a same name (but for use of the ordinal term) to
distinguish the claim elements. As used herein, "and/or" means that
the listed items are alternatives, but the alternatives also
include any combination of the listed items.
* * * * *