METHODS, SYSTEMS, AND MEDIA FOR CONTENT RANKING USING REAL-TIME DATA

• US 20110314007A1
• Filed: 06/16/2011
• Published: 12/22/2011
• Est. Priority Date: 06/16/2010
• Status: Active Grant

• Current Assignee: Rallyverse, Inc.
• Original Assignee: Rallyverse, Inc.
• Inventors: Dassa, Guy, Doran, Joseph P.
• Granted Patent: US 8,756,224 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/40 of multimedia data, e.g. slideshows comprising image and additional audio data retrieval of still image data G06F16/50; retrieval of audio data G06F16/60; retrieval of video data G06F16/70
• CPC Class Codes: G06F 16/972 Access to data in other repository systems, e.g. legacy data or dynamic Web page generation

Abstract

Methods, systems, and media for content ranking using real-time data are provided. In accordance with some embodiments of the present invention, a method, implemented on a processor, for ranking content is provided. The method can include, among other things: receiving real-time information from a plurality of sources; supplementing the received real-time information with historical information and user influence information; analyzing the supplemented real-time information from the plurality of sources to determine real-time trend information; receiving a plurality of content snippets from a content provider; detecting similarities between each of the plurality of content snippets and the determined real-time trend information; ranking the plurality of content snippets based on the detected similarities; and displaying the ranked plurality of content snippets.

Claims

1. A method for ranking content, the method comprising:

receiving real-time information from a plurality of sources;

supplementing the received real-time information with historical information and user influence information;

analyzing the supplemented real-time information from the plurality of sources to determine real-time trend information;

receiving a plurality of content snippets from a content provider;

detecting similarities between each of the plurality of content snippets and the determined real-time trend information;

ranking the plurality of content snippets based on the detected similarities; and

displaying the ranked plurality of content snippets.

2. The method of claim 1, wherein the received real-time information includes at least one of structured real-time information and unstructured real-time information.

3. The method of claim 1, wherein the plurality of content snippets from a content provider comprises receiving the plurality of content snippets from a data feed.

4. The method of claim 3, wherein the data feed is one of:

a Really Simple Syndication (RSS) feed, an Atom feed, an Extensible Markup Language (XML) feed, and data provided in JavaScript Object Notation (JSON) format.

5. The method of claim 1, wherein the plurality of sources providing real-time information comprise one or more of:

a social media network, a social messaging service, a social content sharing service, an e-mail message, an instant message, a short message service (SMS) message, a web service, a weblog, and a search engine.

6. The method of claim 1, wherein the user influence information includes personally related information received or derived from a user.

7. The method of claim 6, further comprising ranking the plurality of content snippets based on the detected similarities with the determined real-time trend information and based on the historical and personally related information received or derived from the user.

8. The method of claim 1, further comprising generating an index of the determined real-time trend information, wherein a plurality of keywords are extracted from the supplemented real-time information and an association between the plurality of keywords is created to generate the index.

9. The method of claim 8, further comprising detecting similarities between each of the plurality of content snippets and the determined real-time trend information by extracting at least one keyword from each of the plurality of content snippets, calculating a similarity score based on a comparison of the extract keyword with each trend in the generated index, and aggregating the similarity score for each trend to generate an aggregated similarity score, wherein the plurality of content snippets are ranked based at least in part on the aggregated similarity score.

10. The method of claim 1, further comprising:

receiving a plurality of data feeds from a plurality of web sources;

retrieving content snippets from each of the plurality of data feeds;

ranking the retrieved content snippets, wherein the ranking comprises;

detecting similarities between each of the plurality of content snippets and real-time trend information from a trend index;

generating a personal relevance score for each content snippet; and

sorting each of the plurality of content snippets into a content listing based on the personal relevance score; and

displaying the ranked content snippets.

11. The method of claim 1, further comprising:

displaying a list containing unranked content snippets, wherein the content snippets are the content snippets in the ranked content snippets;

receiving feedback from a plurality of users with respect to the list containing the unranked content snippets; and

using the received feedback to determine performance of one or more models used to rank the content snippets.

12. A system for ranking content, the system comprising:

a processor that;

receives real-time information from a plurality of sources;

analyzes the real-time information from the plurality of sources to determine real-time trend information;

receives a plurality of content snippets from a content provider;

detects similarities between each of the plurality of content snippets and the determined real-time trend information;

ranks the plurality of content snippets based on the detected similarities; and

displays the ranked plurality of content snippets.

13. The system of claim 12, wherein the received real-time information includes at least one of structured real-time information and unstructured real-time information.

14. The system of claim 12, wherein the plurality of content snippets from a content provider comprises receiving the plurality of content snippets from a data feed.

15. The system of claim 14, wherein the data feed is one of:

a Really Simple Syndication (RSS) feed, an Atom feed, an Extensible Markup Language (XML) feed, and data provided in JavaScript Object Notation (JSON) format.

16. The system of claim 12, wherein the plurality of sources providing real-time information comprise one or more of:

a social media network, a social messaging service, a social content sharing service, an e-mail message, an instant message, a short message service (SMS) message, a web service, a weblog, and a search engine.

17. The system of claim 12, wherein the user influence information includes personally related information received or derived from a user.

18. The system of claim 17, wherein the processor is further configured to rank the plurality of content snippets based on the detected similarities with the determined real-time trend information and based on the historical and personally related information received or derived from the user.

19. The system of claim 12, wherein the processor is further configured to generate an index of the determined real-time trend information, wherein a plurality of keywords are extracted from the supplemented real-time information and an association between the plurality of keywords is created to generate the index.

20. The system of claim 19, wherein the processor is further configured to detect similarities between each of the plurality of content snippets and the determined real-time trend information by extracting at least one keyword from each of the plurality of content snippets, calculating a similarity score based on a comparison of the extract keyword with each trend in the generated index, and aggregating the similarity score for each trend to generate an aggregated similarity score, wherein the plurality of content snippets are ranked based at least in part on the aggregated similarity score.

21. The system of claim 12, wherein the processor is further configured to:

receive a plurality of data feeds from a plurality of web sources;

retrieve content snippets from each of the plurality of data feeds;

rank the retrieved content snippets, wherein the processor is further configured to;

detect similarities between each of the plurality of content snippets and real-time trend information from a trend index;

generate a personal relevance score for each content snippet; and

sort each of the plurality of content snippets into a content listing based on the personal relevance score; and

display the ranked content snippets.

22. The system of claim 12, wherein the processor is further configured to:

display a list containing unranked content snippets, wherein the content snippets are the content snippets in the ranked content snippets;

receive feedback from a plurality of users with respect to the list containing the unranked content snippets; and

use the received feedback to determine performance of one or more models used to rank the content snippets.

23. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for ranking content, the method comprising:

receiving real-time information from a plurality of sources;

analyzing the real-time information from the plurality of sources to determine real-time trend information;

receiving a plurality of content snippets from a content provider;

detecting similarities between each of the plurality of content snippets and the determined real-time trend information;

ranking the plurality of content snippets based on the detected similarities; and

displaying the ranked plurality of content snippets.