System and Method for Context-Aware Recommendation through User Activity Change Detection
First Claim
1. A method comprising:
- receiving, by one or more processors of a computing device, a recommendation request corresponding to a user;
retrieving a user profile of the user based on the recommendation request, the user profile comprising user preference data of the user associated with one or more items and user demographic information of the user;
computing a utility value of an item based on the user profile and item models built based on user preference data of a plurality of users and item information of a plurality of items; and
selecting a subset of items with highest utility values as the recommendation list.
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Abstract
Example systems and methods for context-aware recommendation generation are described. In one implementation, item models are built using user preference data of multiple users and item information of multiple items. When a recommendation request corresponding to a user is received, the profile of that user is retrieved from the user profile database. Given the profile of the user and the item models, utility scores are then computed for the candidate items. Our system exploits a novel approach to detect any sudden and significant changes in the preference data of the given user. If a change is detected, the utility scores are adapted to prioritize the user'"'"'s most recent preferences. The computed utility scores are used as the basis for ranking the items. A subset of items with highest scores is then selected as recommendations and is presented to the user.
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Citations
18 Claims
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1. A method comprising:
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receiving, by one or more processors of a computing device, a recommendation request corresponding to a user; retrieving a user profile of the user based on the recommendation request, the user profile comprising user preference data of the user associated with one or more items and user demographic information of the user; computing a utility value of an item based on the user profile and item models built based on user preference data of a plurality of users and item information of a plurality of items; and selecting a subset of items with highest utility values as the recommendation list. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. An apparatus comprising:
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a memory configured to store data and one or more sets of instructions; and one or more processors coupled to the memory, the one or more processors configured to execute the one or more sets of instructions and perform operations comprising; receiving, by one or more processors of a computing device, a recommendation request corresponding to a user, retrieving a user profile of the user based on the recommendation request, the user profile comprising user preference data of the user associated with one or more items and user demographic information of the user, computing a value of an item based on the user profile and item models built based on user preference data of a plurality of users and item information of a plurality of items, and generating a recommendation associated with the item based on the value.
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- 18. The apparatus of claim 19, wherein the additional user profile excludes user preference data that is collected before the user activity change is detected.
Specification