Method for Finding Mood-Dependent "top" (-selling/rated) "lists"

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A system and method for determining a rank aggregation from a series of partial preferences is presented. A distribution is learned over preferences from partial preferences with sparse support. A computer receives a plurality of partial preferences selected from two or more preference lists. Weights are assigned to each of said plurality of partial preferences, resulting in multiple ranked lists.

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 finding mood-dependent top selling/rated lists
    United States of America | Granted | 9,201,968

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