USER BEHAVIOR MODEL FOR CONTEXTUAL PERSONALIZED RECOMMENDATION

摘要

A user behavior model provides personalized recommendations based in part on time and location, particularly to users of mobile devices. Entity types are ranked according to relevance to the user. Example entity types are restaurant, hotel, etc. The relevance may be based on reference to a large-scale database containing queries from other users. Additionally, entities within each entity type may be ranked based on relevance to the user and the time and location context. A user interface may display a ranked list of entity types, such as restaurant, hotel, etc., wherein each entity type is represented by a highest-ranked entity with the entity type. Thus, the user interface may display a highest-ranked restaurant, a highest-ranked hotel, etc. Upon user selection of one such entity type the user interface is replaced with a second user interface, for example showing a ranked hierarchy of restaurants, headed by the highest-ranked restaurant.

主权项

1. A method comprising:
referencing context information associated with a user; ranking entity types according to relevance to the user, the relevance to the user of the ranked entity types based in part on the context information; ranking entities within each entity type according to relevance to the user, the relevance to the user of ranked entities within each entity type based in part on the context information; representing each entity type with a most relevant entity within a respective entity type according to the ranking of entities within the respective entity type for display at a user interface; and causing display, within the user interface, of a listing of most relevant entities according to a ranking of entity types corresponding to the most relevant entities in the listing respectively.