New Methodology for Personalized Recommendation

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A system and method for providing a personalized recommendation from a series of partial preferences is presented. A preference distribution of a population including a plurality of weighted ranked lists is identified. A revealed preference of a user is compared to the plurality of ranked lists. An affinity weight between the user and each of the plurality of ranked lists is assigned, and a weighted average of each of the affinity weights is taken.

Researchers

Devavrat Shah / Srikanth Jagabathula / Vivek F. Farias / Ammar Ammar

Departments: Dept of Electrical Engineering & Computer Science, Sloan School of Management
Technology Areas: Artificial Intelligence (AI) and Machine Learning (ML) / Computer Science: Networking & Signals
Impact Areas: Connected World

  • system and method for providing personalized recommendations
    United States of America | Granted | 9,251,527

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