INFORMATION RECOMMENDATION METHOD, RECOMMENDATION ENGINE, NETWORK SYSTEM

• US 20130031173A1
• Filed: 06/22/2012
• Published: 01/31/2013
• Est. Priority Date: 07/30/2011
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: DENG, Rong
• Granted Patent: US 8,812,592 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

An information recommendation method, a recommendation engine, and a network system are disclosed in embodiments of the present invention. The method includes: acquiring a friend list of a user from a data source with a social relationship; acquiring a behavior record of a friend in the friend list of the user from a user behavior database; generating recommendation information matched with current behavior of the user, according to the behavior record of the friend in the friend list of the user and information of the current behavior of the user; and sending the recommendation information to an application website. Through the embodiments of the present invention, when information is recommended to a user, the recommendation information can be generated based on the social relationship and according to the behavior record of the friend of the user.

Claims

1. An information recommendation method, comprising:

acquiring a friend list of a user from a data source with a social relationship;

acquiring a behavior record of a friend in the friend list of the user from a user behavior database;

generating recommendation information matched with current behavior of the user, according to the behavior record of the friend in the friend list of the user and information of the current behavior of the user; and

sending the recommendation information to an application website.

2. The information recommendation method according to claim 1, wherein before the acquiring the friend list of the user from the data source with the social relationship, the method comprises:

receiving a request message that is used for acquiring recommendation information and is sent by the application website, wherein the request message carries the information of the current behavior of the user;

or

subscribing to the friend list of the user from the data source with the social relationship.

3. The information recommendation method according to claim 1, wherein the acquiring the friend list of the user from the data source with the social relationship comprises:

sending a request message used for acquiring the friend list of the user to at least one data source with the social relationship, wherein the request message carries identity authentication information of the user in the at least one data source with the social relationship; and

receiving the friend list of the user returned by the at least one data source with the social relationship.

4. The information recommendation method according to claim 1, wherein the acquiring the friend list of the user from the data source with the social relationship further comprises:

receiving a notification on change of the friend list of the user when the friend list of the user is changed, wherein the notification is actively sent by at least one data source with the social relationship; and

updating the friend list of the user according to the notification on the change.

5. The information recommendation method according to claim 3, wherein if repetitive friends exist in the friend list of the user, one of the repetitive friends is retained and the rest is deleted.

6. The information recommendation method according to claim 1, wherein the acquiring the behavior record of the friend in the friend list of the user from the user behavior database comprises:

sending request information for acquiring the behavior record of the friend in the friend list of the user to the user behavior database, wherein the request information carries the friend list of the user; and

receiving the behavior record of the friend that is in the friend list of the user and is returned by the user behavior database.

7. The information recommendation method according to claim 1, wherein the generating the recommendation information matched with the current behavior of the user, according to the behavior record of the friend in the friend list of the user and the information of the current behavior of the user comprises:

selecting a target friend behavior record matched with a current behavior record of the user from the behavior records of the friends in the friend list of the user, and generating the recommendation information by using the target friend behavior record.

8. The information recommendation method according to claim 7, wherein the selecting the target friend behavior record matched with the current behavior record of the user from the behavior records of the friends in the friend list of the user and generating the recommendation information by using the target friend behavior record comprises:

setting, by a user, that a behavior record of a specific friend is preferably generated; and

setting, by a user, a friend behavior record in a specific period of time.

9. A recommendation engine, comprising:

a friend list acquisition unit, configured to acquire a friend list of a user from a data source with a social relationship;

a friend behavior record acquisition unit, configured to acquire a behavior record of a friend in the friend list of the user from a user behavior database;

a recommendation information generation unit, configured to generate recommendation information matched with current behavior of the user, according to the behavior record of the friend in the friend list of the user and information of the current behavior of the user; and

a recommendation information sending unit, configured to send the recommendation information to an application website.

10. The recommendation engine according to claim 9, further comprising:

a request message receiving unit, configured to receive a request message that is used for acquiring recommendation information and is sent by the application website, wherein the request message carries the information of the current behavior of the user; and

a friend list subscription unit, configured to subscribe to the friend list of the user from the data source with the social relationship.

11. The recommendation engine according to claim 9, wherein the friend list acquisition unit comprises:

a friend list request message sending module, configured to send a request message used for acquiring the friend list of the user to at least one data source with the social relationship, wherein the request message carries identity authentication information of the user in the at least one data source with the social relationship; and

a friend list receiving module, configured to receive the friend list of the user returned by the at least one data source with the social relationship.

12. The recommendation engine according to claim 9, wherein the friend list acquisition unit further comprises:

a change notification receiving module, configured to receive a notification on change of the friend list of the user when the friend list of the user is changed, where the notification is actively sent by at least one data source with the social relationship; and

update the friend list of the user according to the notification on the change.

13. The recommendation engine according to claim 11, further comprising:

a repetition removing unit, configured to, when repetitive friends exist in the friend list of the user, retain one of the repetitive friends and delete other repetitive friends.

14. The recommendation engine according to claim 9, wherein the friend behavior record acquisition unit further comprises:

a behavior record acquisition request sending module, configured to send request information for acquiring the behavior record of the friend in the friend list of the user to the user behavior database, wherein the request information carries the friend list of the user; and

a behavior record receiving module, configured to receive the behavior record of the friend that is in the friend list of the user and is returned by the user behavior database.

15. The recommendation engine according to claim 9, wherein the recommendation information generation unit is specifically configured to:

select a target friend behavior record matched with a current behavior record of the user from the behavior records of the friends in the friend list of the user, and generate the recommendation information by using the target friend behavior record.

16. A network system, comprising:

a recommendation engine, configured to;

acquire a friend list of a user from a data source with a social relationship;

acquire a behavior record of a friend in the friend list of the user from a user behavior database;

generate recommendation information matched with current behavior of the user, according to the behavior record of the friend in the friend list of the user and information of the current behavior of the user; and

send the recommendation information to an application website; and

the data source with the social relationship, configured to receive a request message that is used for acquiring the friend list of the user and is sent by the recommendation engine, and send the friend list of the user to the recommendation engine.

17. The network system according to claim 16, further comprising:

the application website, configured to send a request message used for acquiring the recommendation information to the recommendation engine, then receive the recommendation information sent by the recommendation engine, and display the recommendation information to a user; and

the user behavior database, configured to receive request information that is used for acquiring the behavior record of the friend in the friend list of the user and is sent by the recommendation engine, send the behavior record of the friend in the friend list of the user to the recommendation engine, and store the behavior record of the user of the data source with the social relationship.