CLUSTER-BASED IDENTIFICATION OF NEWS STORIES
First Claim
1. A method in a content recommendation system, the method comprising:
- identifying a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising;
processing content items to determine semantic information that includes identified entities and relations between the identified entities;
storing the identified entities and relations in a repository of the content recommendation system;
generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items; and
storing an indication of the identified news story and the generated cluster.
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Abstract
Methods, systems, and techniques for cluster-based content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend news stories about events or occurrences. In some embodiments, a news story about an event includes multiple related content items that each include an account of the event and that each reference one or more entities or categories that are represented by the CRS. In one embodiment, the CRS identifies news stories by generating clusters of related content items. Then, in response to a received query that indicates a keyterm, entity, or category, the CRS determines and provides indications of one or more news stories that are relevant to the received query. In some embodiments, at least some of these techniques are employed to implement a news story recommendation facility in an online news service.
169 Citations
29 Claims
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1. A method in a content recommendation system, the method comprising:
identifying a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising; processing content items to determine semantic information that includes identified entities and relations between the identified entities; storing the identified entities and relations in a repository of the content recommendation system; generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items; and storing an indication of the identified news story and the generated cluster. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A method in a content recommendation system for recommending a news story about an event, the news story including multiple content items that each give an account of the event, and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising:
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receiving a search query that includes an indication of an entity or a category; selecting the news story from a plurality of news stories, the selecting based on how many entities or categories are in common between the received search query and the multiple content items of the selected news story; and transmitting an indication of the selected news story. - View Dependent Claims (21)
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22. A computer-readable medium including contents that enable a computing system to recommend content, by performing the method comprising:
identifying a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising; processing content items to determine semantic information that includes identified entities and relations between the identified entities; storing the identified entities and relations in a repository of the content recommendation system; generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items; and storing an indication of the identified news story and the generated cluster. - View Dependent Claims (23, 24)
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25. A computing system configured to recommend content, comprising:
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a memory; a module stored on the memory that is configured, when executed, to identify a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, by; processing content items to determine semantic information that includes identified entities and relations between the identified entities; storing the identified entities and relations in a repository of the content recommendation system; generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items; and storing an indication of the identified news story and the generated cluster. - View Dependent Claims (26, 27, 28, 29)
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Specification