METHOD AND SYSTEM FOR PROVIDING A PERSONALIZED SNIPPET

• US 20160283585A1
• Filed: 07/08/2014
• Published: 09/29/2016
• Est. Priority Date: 07/08/2014
• Status: Active Grant

• Current Assignee: Yahoo Assets LLC
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Zheng, Hao
• Granted Patent: US 10,621,220 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/345 Summarisation for human users

Abstract

Methods, systems and programing for providing a personalized snippet are presented. In one example, a request is received for a snippet related to content to be provided to a user. A plurality of portions of the content is obtained. A first score is calculated for each of the plurality of portions based on information about of the user. One or more portions are selected from the plurality of portions based on the calculated first score. The snippet related to the content is created based on the selected one or more portions. The snippet is transmitted as a response to the request.

Claims

1. A method, implemented on a machine having at least one processor, storage, and a communication platform connected to a network for providing a personalized snippet, comprising:

receiving, via the communication platform, a request for a snippet related to content to be provided to a user;

obtaining a plurality of portions of the content;

calculating, for each of the plurality of portions, a first score based on information about of the user;

selecting one or more portions from the plurality of portions based on the calculated first score;

creating the snippet related to the content based on the selected one or more portions; and

transmitting the snippet as a response to the request.

2. The method of claim 1, wherein the first score represents a likelihood that the user will follow a reference to the content if the snippet includes the portion.

3. The method of claim 2, wherein the likelihood is calculated based on at least one of:

characteristics of the user, characteristics of the content, and characteristics of the plurality of portions.

4. The method of claim 1, wherein the selected one or more portions have highest first scores among the plurality of portions.

5. The method of claim 2, further comprising:

providing the reference to the content and the snippet to the user.

6. The method of claim 1, wherein obtaining a plurality of portions of the content includes parsing the content into a plurality of text portions based on a topic of each text portion.

7. The method of claim 1, wherein calculating a first score comprises:

obtaining a user profile and/or a user interest profile of the user;

determining the one or more interests of the user based on the user profile and/or the user interest profile;

obtaining one or more features of each of the plurality of portions; and

calculating, for each of the plurality of portions, a first score based on the one or more features and the one or more interests of the user.

8. The method of claim 1, further comprising:

extracting one or more first features from the content;

obtaining one or more second features of each of the plurality of portions;

comparing, for each of the plurality of portions, the one or more first features with the one or more second features; and

calculating, for each of the plurality of portions, a second score based on results of the comparing, wherein the one or more portions are selected based on the calculated first score and second score.

9. The method of claim 8, wherein the second score calculated for each portion represents a descriptive power of the portion with respect to the content.

10. The method of claim 8, wherein each of the one or more first and second features includes at least one of:

length, position, similarity to a title, containment of name entities, and keywords or categories of the content.

11. The method of claim 8, wherein selecting one or more portions comprises:

generating a first ranking list of the plurality of portions based on the first score of each portion;

generating a second ranking list of the plurality of portions based on the second score of each portion; and

selecting the one or more portions based on the first and second ranking lists.

12. The method of claim 1, wherein creating the snippet comprises:

modifying the selected one or more portions based on knowledge information; and

creating the snippet based on the modified one or more portions based on grammar information.

13. A system, having at least one processor, storage, and a communication platform connected to a network for providing a personalized snippet, comprising:

a snippet request analyzer configured to receive, via the communication platform, a request for a snippet related to content to be provided to a user;

a content parsing unit configured to obtain a plurality of portions of the content;

a user interest-based text ranking unit configured to calculate, for each of the plurality of portions, a first score based on information about the user;

a snippet generation unit configured to select one or more portions from the plurality of portions based on the calculated first score and create the snippet related to the content based on the selected one or more portions; and

a snippet transmitting unit configured to transmit the snippet as a response to the request.

14. The system of claim 13, wherein the first score represents a likelihood that the user will follow a reference to the content if the snippet includes the portion.

15. The system of claim 14, wherein the likelihood is calculated based on at least one of:

characteristics of the user, characteristics of the content, and characteristics of the plurality of portions.

16. The system of claim 13, wherein the selected one or more portions have highest first scores among the plurality of portions.

17. The system of claim 13, wherein calculating a first score comprises:

obtaining a user profile and/or a user interest profile of the user;

determining the one or more interests of the user based on the user profile and/or the user interest profile;

obtaining one or more features of each of the plurality of portions; and

calculating, for each of the plurality of portions, a first score based on the one or more features and the one or more interests of the user.

18. A machine-readable tangible and non-transitory medium having information recorded thereon for providing a personalized snippet of content, wherein the information, when read by the machine, causes the machine to perform the following:

receiving, via the communication platform, a request for a snippet related to content to be provided to a user;

obtaining a plurality of portions of the content;

calculating, for each of the plurality of portions, a first score based on information about of the user;

selecting one or more portions from the plurality of portions based on the calculated first score;

creating the snippet related to the content based on the selected one or more portions; and

transmitting the snippet as a response to the request.

19. The medium of claim 18, wherein the first score represents a likelihood that the user will follow a reference to the content if the snippet includes the portion.

20. The medium of claim 19, wherein the likelihood is calculated based on at least one of:

characteristics of the user, characteristics of the content, and characteristics of the plurality of portions.