COMPATIBILITY ASSESSMENT THROUGH MACHINE LEARNING
Abstract:
Systems, methods, and computer media for determining compatible users through machine learning are provided herein. Previous interactions between some users in a group can be used to determine a first set of user-to-user compatibility scores. Both the first set of compatibility scores and attributes for the users in the group can be provided as inputs to a machine learning model that can be used to determine a second set of user-to-user compatibility scores for user pairs who do not have an interaction history. Along with input constraints, the first and second sets of user-to-user compatibility scores can be used to select compatible user groups.
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