METHOD AND DEVICE FOR PUSHING INFORMATION
The present disclosure discloses a method and device for pushing information to a target user. One example method includes identifying a plurality of users that meet a predetermined condition; selecting a target user from the identified users to be provided with information, where in the target user is selected based on a relationship strength and an influence of the identified users; and transmitting the information to the determined target user over a network, and relates to the field of information technologies.
1 .- 20 . (canceled)
21 . A computer-implemented method, comprising:
identifying a plurality of users satisfying a predetermined condition;
obtaining initial relation community labels of the plurality of users;
determining an updated relation community label for each user of the plurality of users, wherein determining the updated relation community label for each user comprises:
determining that a relationship strength between a first user of the plurality of users and a second user of the plurality of users is larger than a threshold, and
responsive to determining that the relationship strength between the first user and the second user is larger than the threshold, assigning matching updated relation community labels to the first user and the second user;
dividing the plurality of users into a plurality of relation communities, wherein users having matching updated relation community labels are assigned to a particular relation community, wherein each user of the plurality of users is assigned to a single relation community based on the updated relation community label of the user, and wherein at least one of the plurality of relation communities corresponds to membership in an online social network community;
selecting a plurality of target users from the users of each particular relation community to be provided with information, wherein the target users are selected based on respective influences of the target users compared to respective influences of other users of the particular relation community, wherein the influence of each user comprises a strength with which the user affects other users; and
transmitting the information to the selected plurality of target users over a network.
22 . The computer-implemented method of claim 21 , wherein the updated relation community labels are final updated relation community labels, and wherein determining the final updated relation community label for each user of the plurality of users further comprises:
updating, in a predetermined number of iterations, comparisons of relationship strength between the users of the plurality of users, wherein the predetermined number of iterations is at least two, and wherein each iteration after a first iteration of the predetermined number of iterations comprises:
obtaining, for the first user, a previous relation community label based on a previous iteration to the iteration;
determining whether a relationship strength between the first user and another user of the plurality of users is larger than the threshold; and
in response to determining that the relationship strength between the first user and the other user is larger than the threshold, assigning matching updated relation community labels to the first user and the other user, comprising one of
changing the previous relation community label of the first user to match a previous relation community label of the other user, or
changing the previous relation community label of the other user to match the previous relation community label of the first user,
wherein an updated relationship community label of the first user based on a final iteration of the predetermined number of iterations is the final updated relation community label of the first user.
23 . The computer-implemented method of claim 21 , wherein selecting the plurality of target users from each particular relation community to be provided with information comprises:
selecting
,
as
the
plurality
of
target
users
,
a
matching
proportion
of
the
users
of
each
relation
community
.
24 . The computer-implemented method of claim 21 , further comprising:
determining an influence level for each user in the plurality of users based on a predetermined influence level table.
25 . The computer-implemented method of claim 24 , wherein the predetermined influence level table comprises influence threshold intervals that correspond to different influence levels, the different influence levels divided into high, medium, sub-medium, and low.
26 . A non-transitory, computer-readable storage medium coupled to one or more computers and configured with instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
identifying a plurality of users satisfying a predetermined condition;
obtaining initial relation community labels of the plurality of users;
determining an updated relation community label for each user of the plurality of users, wherein determining the updated relation community label for each user comprises:
determining that a relationship strength between a first user of the plurality of users and a second user of the plurality of users is larger than a threshold, and
responsive to determining that the relationship strength between the first user and the second user is larger than the threshold, assigning matching updated relation community labels to the first user and the second user;
dividing the plurality of users into a plurality of relation communities, wherein users having matching updated relation community labels are assigned to a particular relation community, wherein each user of the plurality of users is assigned to a single relation community based on the updated relation community label of the user, and wherein at least one of the plurality of relation communities corresponds to membership in an online social network community;
selecting a plurality of target users from the users of each particular relation community to be provided with information, wherein the target users are selected based on respective influences of the target users compared to respective influences of other users of the particular relation community, wherein the influence of each user comprises a strength with which the user affects other users; and
transmitting the information to the selected plurality of target users over a network.
27 . The non-transitory, computer-readable storage medium of claim 26 , wherein the updated relation community labels are final updated relation community labels, and wherein determining the final updated relation community label for each user of the plurality of users further comprises:
updating, in a predetermined number of iterations, comparisons of relationship strength between the users of the plurality of users, wherein the predetermined number of iterations is at least two, and wherein each iteration after a first iteration of the predetermined number of iterations comprises:
obtaining, for the first user, a previous relation community label based on a previous iteration to the iteration;
determining whether a relationship strength between the first user and another user of the plurality of users is larger than the threshold; and
in response to determining that the relationship strength between the first user and the other user is larger than the threshold, assigning matching updated relation community labels to the first user and the other user, comprising one of
changing the previous relation community label of the first user to match a previous relation community label of the other user, or
changing the previous relation community label of the other user to match the previous relation community label of the first user,
wherein an updated relationship community label of the first user based on a final iteration of the predetermined number of iterations is the final updated relation community label of the first user.
28 . The non-transitory, computer-readable storage medium of claim 26 , wherein selecting the plurality of target users from each particular relation community to be provided with information comprises:
selecting, as the plurality of target users, a matching proportion of the users of each relation community.
29 . The non-transitory, computer-readable storage medium of claim 26 , wherein the operations further comprise:
determining an influence level for each user in the plurality of users based on a predetermined influence level table.
30 . The non-transitory, computer-readable storage medium of claim 29 , wherein the predetermined influence level table comprises influence threshold intervals that correspond to different influence levels, the different influence levels divided into high, medium, sub-medium, and low.
31 . A computer-implemented system, comprising:
one or more computers; and
one or more computer-readable storage media coupled to the one or more computers and configured with instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
identifying a plurality of users satisfying a predetermined condition;
obtaining initial relation community labels of the plurality of users;
determining an updated relation community label for each user of the plurality of users, wherein determining the updated relation community label for each user comprises:
determining that a relationship strength between a first user of the plurality of users and a second user of the plurality of users is larger than a threshold, and
responsive to determining that the relationship strength between the first user and the second user is larger than the threshold, assigning matching updated relation community labels to the first user and the second user;
dividing the plurality of users into a plurality of relation communities, wherein users having matching updated relation community labels are assigned to a particular relation community, wherein each user of the plurality of users is assigned to a single relation community based on the updated relation community label of the user, and wherein at least one of the plurality of relation communities corresponds to membership in an online social network community;
selecting a plurality of target users from the users of each particular relation community to be provided with information, wherein the target users are selected based on respective influences of the target users compared to respective influences of other users of the particular relation community, wherein the influence of each user comprises a strength with which the user affects other users; and
transmitting the information to the selected plurality of target users over a network.
32 . The computer-implemented system of claim 31 , wherein the updated relation community labels are final updated relation community labels, and wherein determining the final updated relation community label for each user of the plurality of users further comprises:
updating, in a predetermined number of iterations, comparisons of relationship strength between the users of the plurality of users, wherein the predetermined number of iterations is at least two, and wherein each iteration after a first iteration of the predetermined number of iterations comprises:
obtaining, for the first user, a previous relation community label based on a previous iteration to the iteration;
determining whether a relationship strength between the first user and another user of the plurality of users is larger than the threshold; and
in response to determining that the relationship strength between the first user and the other user is larger than the threshold, assigning matching updated relation community labels to the first user and the other user, comprising one of
changing the previous relation community label of the first user to match a previous relation community label of the other user, or
changing the previous relation community label of the other user to match the previous relation community label of the first user,
wherein an updated relationship community label of the first user based on a final iteration of the predetermined number of iterations is the final updated relation community label of the first user.
33 . The computer-implemented system of claim 31 , wherein selecting the plurality of target users from each particular relation community to be provided with information comprises:
selecting, as the plurality of target users, a matching proportion of the users of each relation community.
34 . The computer-implemented system of claim 31 , wherein the operations further comprise:
determining an influence level for each user in the plurality of users based on a predetermined influence level table.
35 . The computer-implemented system of claim 34 , wherein the predetermined influence level table comprises influence threshold intervals that correspond to different influence levels, the different influence levels divided into high, medium, sub-medium, and low.