Multi-domain recommendations
First Claim
1. One or more computer-readable storage media having embodied thereon computer-executable instructions that, when executed, perform a method of generating and presenting multi-domain recommendations to a user viewing a topic-of-interest on a Web page, the method comprising:
- identifying the topic-of-interest on the Web page being viewed by the user;
mapping the topic-of-interest to an entity ID in a multi-domain recommendation data structure stored in association with a data store;
using the multi-domain recommendation data structure;
(1) determining one or more entities mapped to the entity ID, wherein an entity comprises at least one of person, object, location, or topic;
(2) determining one or more uniform resource locators (URLs) mapped to the entity ID using a page-to-entity recommendation data structure generated by associating a set of canonical Web pages with the entity ID, associating a first set of relevant URLs to the set of canonical Web pages, associating a second set of relevant URLs to the first set of relevant URLs, and mapping the entity ID to the first set of relevant URLs and the second set of relevant URLs; and
(3) determining one or more search queries mapped to the entity ID;
generating a set of multi-domain recommendations related to the topic-of-interest, the set of multi-domain recommendations comprising at least a portion of the one or more entities, the one or more URLs, and the one or more search queries; and
presenting the set of multi-domain recommendations on the Web page being viewed by the user.
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Accused Products
Abstract
Methods, computer systems, and computer-readable storage media for generating and presenting multi-domain recommendations to a user viewing a Web page are provided. A topic-of-interest is identified on the Web page being viewed by the user. The topic-of-interest is mapped to an entity ID in a multi-domain recommendation data structure. The multi-domain recommendation data structure is used to identify entities, uniform resource locators, and search queries mapped to the entity ID. Multi-domain recommendations are generated using the entities, uniform resource locators, and search queries; the multi-domain recommendations are presented on the Web page being viewed by the user.
35 Citations
19 Claims
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1. One or more computer-readable storage media having embodied thereon computer-executable instructions that, when executed, perform a method of generating and presenting multi-domain recommendations to a user viewing a topic-of-interest on a Web page, the method comprising:
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identifying the topic-of-interest on the Web page being viewed by the user; mapping the topic-of-interest to an entity ID in a multi-domain recommendation data structure stored in association with a data store; using the multi-domain recommendation data structure; (1) determining one or more entities mapped to the entity ID, wherein an entity comprises at least one of person, object, location, or topic; (2) determining one or more uniform resource locators (URLs) mapped to the entity ID using a page-to-entity recommendation data structure generated by associating a set of canonical Web pages with the entity ID, associating a first set of relevant URLs to the set of canonical Web pages, associating a second set of relevant URLs to the first set of relevant URLs, and mapping the entity ID to the first set of relevant URLs and the second set of relevant URLs; and (3) determining one or more search queries mapped to the entity ID; generating a set of multi-domain recommendations related to the topic-of-interest, the set of multi-domain recommendations comprising at least a portion of the one or more entities, the one or more URLs, and the one or more search queries; and presenting the set of multi-domain recommendations on the Web page being viewed by the user. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computerized method carried out by a recommendation engine running on a processor for generating a multi-domain recommendation data structure, the method comprising:
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accessing a data store to identify related uniform resource locators (URLs), wherein related URLs are identified by; (1) identifying URLs frequently selected by users in response to a search query, (2) identifying URLs frequently visited by users in a browser session, and (3) identifying URLs linked to a source URL, analyzing features of the identified URLs to determine a relevance of each of the identified URLs; generating a page-to-page recommendation data structure by mapping each of the identified URLs to one or more of the related, relevant URLs; and using the page-to-page recommendation data structure to generate a page-to-entity recommendation data structure, an entity-to-entity recommendation data structure, and a search query recommendation data structure, wherein using the page-to-page recommendation data structure to generate the page-to-entity recommendation data structure comprises; (1) identifying a set of canonical Web pages associated with an entity ID; (2) identifying a first set of relevant URLs mapped to the set of canonical Web pages using the page-to-page recommendation data structure; (3) identifying a second set of relevant URLs mapped to the first set of relevant URLs using the page-to-page recommendation data structure; and (4) generating the page-to-entity recommendation data structure by mapping the entity ID to the first set of relevant URLs and the second set of relevant URLs. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A system for generating and presenting multi-domain recommendations to a user viewing a topic-of-interest on a Web page, the system comprising:
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a computing device associated with a recommendation engine having one or more processors and one or more computer-readable storage media; and a data store coupled with the recommendation engine, wherein the recommendation engine; generates a page-to-page recommendation data structure, the page-to-page recommendation data structure comprising a mapping of at least a first uniform resource locator (URLs) to one or more related, relevant URLs; generates a page-to-entity recommendation data structure, wherein generating the page-to-entity recommendation data structure comprises;
1) identifying a set of canonical Web pages associated with an entity ID,
2) identifying a first set of relevant URLs mapped to the set of canonical Web pages using the page-to-page recommendation data structure,
3) identifying a second set of relevant URLs mapped to the first set of relevant URLs using the page-to-page recommendation data structure, and
4) mapping the entity ID to the first set of relevant URLs and the second set of relevant URLs;generates an entity-to-entity recommendation data structure, the entity-to-entity recommendation data structure comprising a mapping of the at least the first entity ID to one or more related entities; generates a search query recommendation data structure, the search query recommendation data structure comprising a mapping of the at least the first entity ID to one or more related search queries; aggregates the page-to-page recommendation data structure, the page-to-entity recommendation data structure, the entity-to-entity recommendation data structure, and the search query recommendation data structure to generate a multi-domain recommendation data structure, the multi-domain recommendation data structure comprising at least a mapping of the first entity ID to related, relevant entities, the first entity ID to related, relevant URLs, and the first entity ID to related, relevant search queries; identifies the topic-of-interest on the Web page currently being viewed by the user; maps the topic-of-interest to the first entity ID; generates the multi-domain recommendations using the multi-domain recommendation data structure, the multi-domain recommendations comprising entities related to the topic-of-interest, URLs related to the topic-of-interest, and search queries related to the topic-of-interest; and automatically presents the multi-domain recommendations on the Web page being viewed by the user.
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Specification