U.S. patent application number 14/160816 was filed with the patent office on 2014-05-15 for creating social network groups.
This patent application is currently assigned to Google Inc.. The applicant listed for this patent is Google Inc.. Invention is credited to Rich GOSSWEILER, James Brooks MILLER.
Application Number | 20140133757 14/160816 |
Document ID | / |
Family ID | 49477325 |
Filed Date | 2014-05-15 |
United States Patent
Application |
20140133757 |
Kind Code |
A1 |
GOSSWEILER; Rich ; et
al. |
May 15, 2014 |
CREATING SOCIAL NETWORK GROUPS
Abstract
Embodiments generally relate to creating groups in a social
network system. In one embodiment, a method includes recognizing at
least one person in the at least one photo associated with a target
user in a social network system, where the recognizing is based at
least in part on social relevance. The method also includes
creating a group in the social network system, where the group
includes the at least one person recognized in the at least one
photo. The method also includes associating the group with the
target user.
Inventors: |
GOSSWEILER; Rich;
(Sunnyvale, CA) ; MILLER; James Brooks;
(Sunnyvale, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google Inc. |
Mountain View |
CA |
US |
|
|
Assignee: |
Google Inc.
Mountain View
CA
|
Family ID: |
49477325 |
Appl. No.: |
14/160816 |
Filed: |
January 22, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
13456970 |
Apr 26, 2012 |
8666123 |
|
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14160816 |
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Current U.S.
Class: |
382/190 |
Current CPC
Class: |
G06K 9/00221 20130101;
G06K 9/00671 20130101; G06K 9/00275 20130101; H04L 67/10 20130101;
G06K 9/62 20130101; G06K 9/00677 20130101 |
Class at
Publication: |
382/190 |
International
Class: |
G06K 9/00 20060101
G06K009/00; H04L 29/08 20060101 H04L029/08 |
Claims
1. A method comprising: recognizing at least one person in at least
one photo associated with a target user in a social network system,
wherein the recognizing is based at least in part on social
relevance, wherein the recognizing of the at least one person
includes identifying at least one face, and applying a facial
recognition algorithm to the at least one face, wherein the
applying of the facial recognition algorithm to the at least one
face comprises: matching facial features of the at least one face
to facial features of at least one known face in a database,
wherein the at least one known face is associated with a candidate
person; determining a degree of social relevance between the
candidate person and the target user; and determining the candidate
person to be the at least one person in the at least one photo
based on the degree of social relevance. creating a group in the
social network system, wherein the group includes the at least one
person recognized in the at least one photo; enabling the target
user to verify that the at least one person recognized in the at
least one photo is correctly recognized; enabling the target user
to modify identification information associated with one or more
people in the group if any person is incorrectly recognized; and
associating the group with the target user.
2. A method comprising: recognizing at least one person in at least
one photo associated with a target user in a social network system,
wherein the recognizing is based at least in part on social
relevance; creating a group in the social network system, wherein
the group includes the at least one person recognized in the at
least one photo; and associating the group with the target
user.
3. The method of claim 2, wherein the obtaining of the at least one
photo comprises obtaining the at least one photo from a camera
device when the target user takes the at least one photo.
4. The method of claim 2, wherein the recognizing of the at least
one person comprises: identifying at least one face; and applying a
facial recognition algorithm to the at least one face.
5. The method of claim 2, wherein the recognizing is based at least
in part on a degree of social relevance between a candidate person
and the target user.
6. The method of claim 2, wherein the recognizing of the at least
one person comprises: identifying at least one face; and applying a
facial recognition algorithm to the at least one face, wherein the
applying of the facial recognition algorithm to the at least one
face comprises: matching facial features of the at least one face
to facial features of at least one known face in a database,
wherein the at least one known face is associated with a candidate
person; determining the degree of social relevance between the
candidate person and the target user; and determining the candidate
person to be the at least one person in the at least one photo
based on the degree of social relevance.
7. The method of claim 2, further comprising enabling the target
user to verify that the at least one person recognized in the at
least one photo is correctly recognized.
8. The method of claim 2, further comprising: enabling the target
user to verify that the at least one person recognized in the at
least one photo is correctly recognized; and enabling the target
user to modify identification information associated with one or
more people in the group if any person is incorrectly
recognized.
9. The method of claim 2, further comprising providing the group to
the target user.
10. The method of claim 2, further comprising notifying the at
least one person recognized in the at least one photo that the
group has been created.
11. The method of claim 2, further comprising sending an invitation
to join the group to the target user and the at least one person
recognized in the at least one photo.
12. A system comprising: one or more processors; and logic encoded
in one or more tangible media for execution by the one or more
processors and when executed operable to perform operations
comprising: recognizing at least one person in the at least one
photo associated with a target user in a social network system,
wherein the recognizing is based at least in part on social
relevance; creating a group in the social network system, wherein
the group includes the at least one person recognized in the at
least one photo; and associating the group with the target
user.
13. The system of claim 12, wherein, to obtain the at least one
photo, the logic when executed is further operable to perform
operations comprising obtaining the at least one photo from a
camera device when the target user takes the at least one
photo.
14. The system of claim 12, wherein, to recognize the at least one
person, the logic when executed is further operable to perform
operations comprising: identifying at least one face; and applying
a facial recognition algorithm to the at least one face.
15. The system of claim 12, wherein the recognizing is based at
least in part on social relevance between a candidate person and
the target user.
16. The system of claim 12, wherein, to recognize the at least one
person, the logic when executed is further operable to perform
operations comprising: identifying at least one face; and applying
a facial recognition algorithm to the at least one face, wherein
the applying of the facial recognition algorithm to the at least
one face comprises: matching facial features of the at least one
face to facial features of at least one known face in a database,
wherein the at least one known face is associated with a candidate
person; determining the degree of social relevance between the
candidate person and the target user; and determining the candidate
person to be the at least one person in the at least one photo
based on the degree of social relevance.
17. The system of claim 12, wherein the logic when executed is
further operable to perform operations comprising enabling the
target user to verify that the at least one person recognized in
the at least one photo is correctly recognized.
18. The system of claim 12, wherein the logic when executed is
further operable to perform operations comprising: enabling the
target user to verify that the at least one person recognized in
the at least one photo is correctly recognized; and enabling the
target user to modify identification information associated with
one or more people in the group if any person is incorrectly
recognized.
19. The system of claim 12, wherein the logic when executed is
further operable to perform operations comprising providing the
group to the target user.
20. The system of claim 12, wherein the logic when executed is
further operable to perform operations comprising notifying the at
least one person recognized in the at least one photo that the
group has been created.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] The present application is a continuation of U.S. patent
application Ser. No. 13/456,970, filed on Apr. 26, 2012, which is
hereby incorporated by reference in its entirety.
TECHNICAL FIELD
[0002] Embodiments relate generally to social network systems, and
more particularly to creating groups in a social network
system.
BACKGROUND
[0003] Social network systems typically enable users to create
social network groups. For example, such social network groups may
include groups of friends or groups of contacts. To create a group,
a user of a social network system typically finds other users by
performing a search, and then invites them to connect socially as
friends or as contacts. A recipient of an invitation can respond by
accepting the invitation, which creates a social connection. Once
the social connection is made, the users can belong to each others
groups and can engage via various social activities. For example,
users can visit each other's profile pages, follow each other's
posts, send messages to each other, etc.
SUMMARY
[0004] Embodiments generally relate to creating groups in a social
network system. In one embodiment, a method includes recognizing at
least one person in at least one photo associated with a target
user in a social network system, where the recognizing is based at
least in part on social relevance; creating a group in the social
network system, where the group includes the at least one person
recognized in the at least one photo; and associating the group
with the target user.
[0005] With further regard to the method, in one embodiment, the
obtaining of the at least one photo includes obtaining the at least
one photo from a camera device when the target user takes the at
least one photo. In one embodiment, the recognizing of the at least
one person includes: identifying at least one face; and applying a
facial recognition algorithm to the at least one face. In one
embodiment, the recognizing is based at least in part on a degree
of social relevance between a candidate person and the target user.
In one embodiment, the recognizing of the at least one person
includes: identifying at least one face; and applying a facial
recognition algorithm to the at least one face, where the applying
of the facial recognition algorithm to the at least one face
includes: matching facial features of the at least one face to
facial features of at least one known face in a database, where the
at least one known face is associated with a candidate person;
determining the degree of social relevance between the candidate
person and the target user; and determining the candidate person to
be the at least one person in the at least one photo based on the
degree of social relevance.
[0006] With further regard to the method, in one embodiment, the
method also includes enabling the target user to verify that the at
least one person recognized in the at least one photo is correctly
recognized. In one embodiment, the method also includes enabling
the target user to verify that the at least one person recognized
in the at least one photo is correctly recognized; and enabling the
target user to modify identification information associated with
one or more people in the group if any person is incorrectly
recognized. In one embodiment, the method also includes providing
the group to the target user. In one embodiment, the method also
includes notifying the at least one person recognized in the at
least one photo that the group has been created. In one embodiment,
the method also includes sending an invitation to join the group to
the target user and the at least one person recognized in the at
least one photo.
[0007] In another embodiment, a method also includes recognizing at
least one person in at least one photo associated with a target
user in a social network system, where the recognizing is based at
least in part on social relevance, where the recognizing of the at
least one person includes identifying at least one face, and
applying a facial recognition algorithm to the at least one face.
In one embodiment, the applying of the facial recognition algorithm
to the at least one face includes: matching facial features of the
at least one face to facial features of at least one known face in
a database, where the at least one known face is associated with a
candidate person; determining a degree of social relevance between
the candidate person and the target user; and determining the
candidate person to be the at least one person in the at least one
photo based on the degree of social relevance. In another
embodiment, a method also includes: creating a group in the social
network system, where the group includes the at least one person
recognized in the at least one photo; enabling the target user to
verify that the at least one person recognized in the at least one
photo is correctly recognized; enabling the target user to modify
identification information associated with one or more people in
the group if any person is incorrectly recognized; and associating
the group with the target user.
[0008] In another embodiment, a system includes one or more
processors, and logic encoded in one or more tangible media for
execution by the one or more processors. When executed, the logic
is operable to perform operations including: recognizing at least
one person in the at least one photo associated with a target user
in a social network system, where the recognizing is based at least
in part on social relevance; creating a group in the social network
system, where the group includes the at least one person recognized
in the at least one photo; and associating the group with the
target user.
[0009] With further regard to the system, in one embodiment, to
obtain the at least one photo, the logic when executed is further
operable to perform operations comprising obtaining the at least
one photo from a camera device when the target user takes the at
least one photo. In one embodiment, to recognize the at least one
person, the logic when executed is further operable to perform
operations comprising: identifying at least one face; and applying
a facial recognition algorithm to the at least one face. In one
embodiment, the recognizing is based at least in part on social
relevance between a candidate person and the target user. In one
embodiment, to recognize the at least one person, the logic when
executed is further operable to perform operations comprising:
identifying at least one face; and applying a facial recognition
algorithm to the at least one face. In one embodiment, the applying
of the facial recognition algorithm to the at least one face
includes: matching facial features of the at least one face to
facial features of at least one known face in a database, where the
at least one known face is associated with a candidate person;
determining the degree of social relevance between the candidate
person and the target user; and determining the candidate person to
be the at least one person in the at least one photo based on the
degree of social relevance.
[0010] With further regard to the system, in one embodiment, the
logic when executed is further operable to perform operations
comprising enabling the target user to verify that the at least one
person recognized in the at least one photo is correctly
recognized. In one embodiment, the logic when executed is further
operable to perform operations comprising: enabling the target user
to verify that the at least one person recognized in the at least
one photo is correctly recognized; and enabling the target user to
modify identification information associated with one or more
people in the group if any person is incorrectly recognized. In one
embodiment, the logic when executed is further operable to perform
operations comprising providing the group to the target user. In
one embodiment, the logic when executed is further operable to
perform operations comprising notifying the at least one person
recognized in the at least one photo that the group has been
created.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 illustrates a block diagram of an example network
environment, which may be used to implement the embodiments
described herein.
[0012] FIG. 2 illustrates an example simplified flow diagram for
creating groups in a social network system, according to one
embodiment.
[0013] FIG. 3 illustrates an example simplified flow diagram for
applying a facial recognition algorithm to one or more faces,
according to one embodiment.
[0014] FIG. 4 illustrates a block diagram of an example server
device, which may be used to implement the embodiments described
herein.
DETAILED DESCRIPTION
[0015] Embodiments described herein facilitate the creation of
social network groups in a social network system. In various
embodiments, a system generates groups for users of the social
network system in response to photos associated with the users. For
example, the system may generate a group that includes friends
shown in a photo.
[0016] As described in more detail below, in one embodiment, the
system recognizes one or more people in one or more photos
associated with a target user in a social network system. For
example, the photos may be associated with the target user in that
the target user took the photos and/or uploaded the photos to the
social network system.
[0017] In one embodiment, the recognizing of the people is based at
least in part on social relevance. For example, for each face
(i.e., image of a face) in a photo, the system matches facial
features of the face to facial features of at least one known face
in a database, where the known face is associated with a candidate
person. In some situations, where there are multiple candidates,
the system determines a degree of social relevance between one or
more candidates and the target user. The system then determines a
candidate person to be a particular person in the photo based on
the degree of social relevance. For example, if the target user and
the candidate person are in each other's personal social network,
there would be a high degree of social relevance and thus a high
probability that the candidate person is the particular person in
the photo. The system then creates a social network group that
includes the one or more people recognized in the photo, and then
associates the group with the target user.
[0018] FIG. 1 illustrates a block diagram of an example network
environment 100, which may be used to implement the embodiments
described herein. In one embodiment, network environment 100
includes a system 102, which includes a server device 104 and a
social network database 106. The term system 102 and phrase "social
network system" may be used interchangeably. Network environment
100 also includes client devices 110, 120, 130, and 140, which may
take photos and upload the photos to system 102 via a network 150.
Client devices 110, 120, 130, and 140 may be camera devices. Client
devices 110, 120, 130, and 140 may also be mobile phones, tablets,
notebook computers, or any other electronic devices having camera
capabilities. In various embodiments, users U1, U2, U3, and U4 may
take photos using respective client devices 110, 120, 130, and 140,
and upload the photos to system 102.
[0019] As described in embodiments herein, users U1, U2, U3, and U4
may have their images captured and then recognized in various
combinations of photos. For example, a group 160 of users U1 and U2
may be recognized in one photo taken by a target user, while a
group 170 of users U3 and U4 may be recognized in another photo
taken by the target user. For ease of illustration, FIG. 1 shows
users U1 and U2 in group 160 and shows users U3 and U4 in group
170. Each of groups 160 and 170 may have any number of users and
have any combination of users U1, U2, U3, and U4, as well as other
users. As described in more detail below, system 102 may create
groups (i.e., social network groups) corresponding to the groups of
users recognized on the photos. For example, system 102 may create
a first social network group that includes users U1 and U2 and may
create a second social network group that includes users U3 and U4.
System 102 may then select one or both groups to present to the
target user, and the target user may in turn select one or both
groups to associate with the target user.
[0020] For ease of illustration, FIG. 1 shows one block for each of
system 102, server device 104, and social network database 106, and
shows four blocks for client devices 110, 120, 130, and 140. Blocks
102, 104, and 106 may represent multiple systems, server devices,
and social network databases. Also, there may be any number of
client devices. In other embodiments, network environment 100 may
not have all of the components shown and/or may have other elements
including other types of elements instead of, or in addition to,
those shown herein.
[0021] FIG. 2 illustrates an example simplified flow diagram for
creating groups in a social network system, according to one
embodiment. Referring to both FIGS. 1 and 2, a method is initiated
in block 202, where system 102 recognizes one or more people in one
or more photos associated with a target user in the social network
system. In one embodiment, the photos are associated with the
target user in that the target user took the photos and/or uploaded
the photos to system 102.
[0022] In one embodiment, system 102 may obtain the one or more
photos from a camera device when the target user takes the one or
more photos. In various embodiments, the camera device may be
implemented with a mobile phone, a tablet, a notebook computer, or
any other suitable electronic device. In some situations, a camera
device may automatically upload photos to system 102 when photos
are taken. In one embodiment, older photos may also be used. For
example, system 102 may receive a pre-existing photo that is
uploaded or scanned by a user.
[0023] In one embodiment, to recognize the one or more people,
system 102 identifies one or more faces, and applies a facial
recognition algorithm to the one or more faces in the photo. Note
that the term "face" and "image of a face" is used
interchangeably.
[0024] In various embodiments, system 102 enables users of the
social network system to opt-in or opt-out of system 102 using
their faces in photos or using their identity information in
recognizing people identified in photos. Also, system 102 enables
users of the social network to opt-in or opt-out of system 102
using their photos for facial recognition in general.
[0025] In one embodiment, for each face in a photo, system 102
analyzes multiple features of the face and generates a feature
vector. In various embodiments, a feature vector is a set of
distinguishing facial characteristics or features, which include
any features that make a face recognizable. Such features may
include, for example, facial hair, skin color, eye color, eye
distance, hair characteristics, etc.
[0026] For each face in a photo, system 102 compares the feature
vector of the identified face to multiple feature vectors of known
faces in a database such as social network database 106 of FIG. 1.
Each known face is associated with a candidate person having a
known user profile in social network database 106.
[0027] In one embodiment, social network database 106 stores images
of known faces, where each known face is associated with a feature
vector. Furthermore, each known face is associated with a known
user of the social network system. For example, the known face is
associated with a known user profile.
[0028] In various embodiments, each feature vector is associated
with a feature vector score, and system 102 compares the feature
vector score of the feature vector of an identified face in a photo
to the feature vector scores associated with known faces. In one
embodiment, system 102 may look up feature vectors of known faces
in a hash table. In one embodiment, system 102 determines the
candidate with the closest feature vector (to that of the
identified face) to be the same person.
[0029] In one embodiment, the feature vector (of the candidate)
with the highest feature vector score has the highest probability
of being associated with a known user. Conversely, the feature
vector with the lowest feature vector score has the lowest
probability of being associated with a known user.
[0030] In some situations, there may be multiple candidates (e.g.,
5 people) with closely matching feature vectors. In other words,
there may be several candidates who look like the person identified
in a given photo. This may be for various reasons. For, example,
some people have very similar features, such as family members.
Also, variations in the quality of a facial image in a photo (e.g.,
lighting, clarity, etc.) cause variations in feature vector
scores.
[0031] In one embodiment, system 102 may obtain time stamp
information and location information associated with each photo.
System 102 may use this information to help in the recognition
process. For example, if system 102 recognizes two possible
candidates for a given face identified in a photo taken at a
particular event, and system 102 knows from the database that one
candidate is in the same city at that time, whereas the other
candidate is in a different city, system 102 can ascertain the best
candidate to associate with the face in the photo.
[0032] Various embodiments described herein, such as those
described in FIG. 3 below, facilitate in narrowing potential
candidates to one candidate.
[0033] FIG. 3 illustrates an example simplified flow diagram for
applying a facial recognition algorithm to one or more faces,
according to one embodiment. Referring to both FIGS. 1 and 3, a
method is initiated in block 302, where, for each face in a photo,
system 102 matches facial features of the face to facial features
of at least one known face in a database (e.g., stored in social
network database 106 of FIG. 1), where the at least one known face
is associated with a candidate person. In one embodiment, the
existing faces may be associated with existing photo albums of the
target user and/or with existing photo albums of any other user or
users of the social network system.
[0034] In various embodiments, system 102 enables users of the
social network to opt-in or opt-out of system 102 using their faces
in photos or using their identity information in recognizing people
identified in photos.
[0035] In block 304, in one embodiment, system 102 may determine a
degree of social relevance between each candidate person and the
target user. In one embodiment, the degree of social relevance may
be a social relevance score. System 102 may determine the social
relevance score based on a weighting function that factors in who
is identified in a given photo and the social connections among the
people in the photo and the target user. In alternative
embodiments, the social relevance score may be based on other
factors such as degrees of separation from the target user, for
example.
[0036] In one scenario, assume user U1 is the target user (who
takes a photo), a person who looks like user U2 (e.g., similar
feature vector scores) is in the photo, and users U1 and U2 know
each other. There would be a high probability that user U2 is
indeed the person in the photo with user U1. Accordingly, system
102 would give user U2 as a candidate a high social relevance
score. The social relevance score of user U2 would be much higher
that the social relevance score of another candidate who looks like
user U2 but who does not know user U1.
[0037] In another scenario, assume user U1 is the target user,
users U2 and a person who looks like U3 are in a photo, user U1
knows user U2 but does not know user U3, user U2 knows U3. In
various embodiments, a given user knows another user in that they
are socially connected (e.g., friends, contacts, etc.) in the
social network system. There would be a fairly high probability
that user U3 is indeed the person in the photo with user U2.
Accordingly, system 102 would give user U3 as a candidate a high
social relevance score. Even if user U1 does know wither users U2
or U3, the fact that users U2 and U3 know each other maintains a
higher social relevance score. In other words, being a friend of a
friend carries weight with regard to the social relevance
score.
[0038] In block 306, system 102 determines a candidate person to be
at least one person in the photo based on the degree of social
relevance. In one embodiment, system 102 may determine the
candidate with the highest social relevance score to be the most
likely to be the same person identified in a photo.
[0039] In various embodiments, system 102 may utilize the degree of
social relevance to recognize a person in a photo based in various
ways. For example, in one embodiment, system 102 may include the
degree of social relevance as a part of feature vectors. In another
embodiment, system 102 may first determine a group of candidates
based on feature vectors without factoring in degrees of social
relevance. System 102 may then narrow down the candidates to one
person based on the degree of social relevance, as described in
FIG. 3.
[0040] Referring again to FIG. 2, in block 204, system 102 creates
one or more groups in the social network system. In one embodiment,
the created groups may be based on the people recognized in the
photos. For example, as described in an example above in connection
with FIG. 1, group 160 of users U1 and U2 may be recognized in one
photo taken by a target user. Also, group 170 of users U3 and U4
may be recognized in another photo taken by the target user. System
102 may create social network groups corresponding to the groups of
users recognized in the photos. For example, system 102 may create
a first group that includes users U1 and U2, and may create a
second group that includes users U3 and U4. In various embodiments,
the target user may be any one of users U1, U2, U3, U4, or another
user of the social network system.
[0041] In various embodiments, system 102 enables people in the
photos to opt-in or opt-out of system 102 adding them to newly
created groups generally and/or to groups associated with
particular users of the social network system.
[0042] A "group" as used in the context of the embodiments
described herein is a social network group. As such, the term
"group" may be used interchangeably with the phrase "social network
group." In various embodiments, a social network group may be a set
of socially connected users in the social network. For example, a
social network group may be a group of friends or a group of
connections.
[0043] In one embodiment, system 102 may create a group based on
multiple pictures from different people. For example, if two users
attend an event and each take photos, system 102 may combine the
people in the photos to create a social network group.
[0044] A benefit of the embodiments described herein is that system
102 creates groups that naturally include people from specific
events, meetings, trips, excursions, and other group activities,
because the groups are based on people recognized in photos often
from such group activities.
[0045] In one embodiment, the one or more groups may include the
target user, because the target user took the photos and probably
knows some if not all people in the photos. In one embodiment, the
one or more groups include at least one person recognized in the
one or more photos. For example, a given group may include at least
one person recognized in the photo and the target user who took the
photo. In some cases, the target user may also be a person
recognized in a photo. This situation may happen, for example,
where the target user has someone else to take the photo so that
the target user is also in the photo. In one embodiment, the one or
more groups may include multiple users recognized in the one or
more photos.
[0046] In one embodiment, system 102 may label each created group.
The label may be a random number, date, location, etc. System 102
also enables the target user to change the label.
[0047] In one embodiment, system 102 enables the target user to
verify that the people recognized in the at least one photo are
correctly recognized. In one embodiment, system 102 causes profile
photos of recognized users to be displayed in association with the
created group. In one embodiment, system 102 includes one or more
photos from which the users in the group where recognized. In one
embodiment, other users in the group may also verify that the
people recognized in the at least one photo are correctly
recognized.
[0048] In one embodiment, system 102 enables the target user to
modify identification information associated with one or more
people in the group if any person is incorrectly recognized. For
example, system 102 may enable the target users to manually add
names to the group.
[0049] In one embodiment, if a face in a photo is not recognized,
system 102 may include a placeholder (e.g., an empty box) in the
group. System 102 may prompt the target user to manually fill in
identifying information for that person. For example, the target
user can look at one or more photos from which the people in the
group were recognized. The target user can then determine which
users are not yet listed in the group. The target user also has the
option of removing the placeholder.
[0050] In block 206, system 102 associates the one or more groups
with the target user. In one embodiment, system 102 may provide the
group to the target user. In various embodiments, system 102 may
enable the target user to include the one or more groups in a list
or cluster of existing groups associated with the target user
(e.g., associated with the profile of the target user). System 102
may cause the list or cluster of groups to be displayed to the
target user in the social network pages of target user. System 102
may enable the target user to elect whether to make each group
associated with the target user visible to other users, and, if
visible, may enable the target user to indicate which other users
are permitted to view the each group.
[0051] In one embodiment, system 102 notifies the people recognized
in the at least one photo that the group has been created. As noted
above, in various embodiments, system 102 enables people in the
photos to opt-in or opt-out of system 102 adding them to newly
created groups generally and/or to groups associated with
particular users of the social network system.
[0052] In one embodiment, system 102 may send an invitation to join
the group to the target user and to the one or more people
recognized in the one or more photos. In such embodiments,
recipients of such invitations may have the option to accept or not
accept the invitations. If a given recipient accepts the
invitation, that user would join the group and be associated with
the group.
[0053] In one embodiment, system 102 enables users to associate
assets with the group. Such assets may include content, for
example, photos, audio tracks, event information, etc. Users who
are included in the group may then access such assets.
[0054] While system 102 is described as performing the steps as
described in the embodiments herein, any suitable component or
combination of components of system 102 or any suitable processor
or processors associated with system 102 may perform the steps
described.
[0055] Although the steps, operations, or computations may be
presented in a specific order, the order may be changed in
particular embodiments. Other orderings of the steps are possible,
depending on the particular implementation. In some particular
embodiments, multiple steps shown as sequential in this
specification may be performed at the same time.
[0056] Embodiments described herein provide various benefits. For
example, embodiments described herein also increase overall
engagement among end-users in a social networking environment by
facilitating the creation of groups among users of the social
network system.
[0057] FIG. 4 illustrates a block diagram of an example server
device 400, which may be used to implement the embodiments
described herein. For example, server device 400 may be used to
implement server device 104 of FIG. 1, as well as to perform the
method embodiments described herein. In one embodiment, server
device 400 includes a processor 402, an operating system 404, a
memory 406, and an input/output (I/O) interface 408. Server device
400 also includes a social network engine 410 and a media
application 412, which may be stored in memory 406 or on any other
suitable storage location or computer-readable medium. Media
application 412 provides instructions that enable processor 402 to
perform the functions described herein and other functions.
[0058] For ease of illustration, FIG. 4 shows one block for each of
processor 402, operating system 404, memory 406, I/O interface 408,
social network engine 410, and media application 412. These blocks
402, 404, 406, 408, 410, and 412 may represent multiple processors,
operating systems, memories, I/O interfaces, social network
engines, and media applications. In other embodiments, server
device 400 may not have all of the components shown and/or may have
other elements including other types of elements instead of, or in
addition to, those shown herein.
[0059] Although the description has been described with respect to
particular embodiments thereof, these particular embodiments are
merely illustrative, and not restrictive. Concepts illustrated in
the examples may be applied to other examples and embodiments.
[0060] Note that the functional blocks, methods, devices, and
systems described in the present disclosure may be integrated or
divided into different combinations of systems, devices, and
functional blocks as would be known to those skilled in the
art.
[0061] Any suitable programming languages and programming
techniques may be used to implement the routines of particular
embodiments. Different programming techniques may be employed such
as procedural or object-oriented. The routines may execute on a
single processing device or multiple processors. Although the
steps, operations, or computations may be presented in a specific
order, the order may be changed in different particular
embodiments. In some particular embodiments, multiple steps shown
as sequential in this specification may be performed at the same
time.
[0062] A "processor" includes any suitable hardware and/or software
system, mechanism or component that processes data, signals or
other information. A processor may include a system with a
general-purpose central processing unit, multiple processing units,
dedicated circuitry for achieving functionality, or other systems.
Processing need not be limited to a geographic location, or have
temporal limitations. For example, a processor may perform its
functions in "real-time," "offline," in a "batch mode," etc.
Portions of processing may be performed at different times and at
different locations, by different (or the same) processing systems.
A computer may be any processor in communication with a memory. The
memory may be any suitable processor-readable storage medium, such
as random-access memory (RAM), read-only memory (ROM), magnetic or
optical disk, or other tangible media suitable for storing
instructions for execution by the processor.
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