18816653. MACHINE LEARNING MODEL FOR RECOMMENDING INTERACTION PARTIES (Capital One Services, LLC)
MACHINE LEARNING MODEL FOR RECOMMENDING INTERACTION PARTIES
Organization Name
Inventor(s)
Dwipam Katariya of McLean VA (US)
Muhammad Uddin of San Bernardino CA (US)
Tania Cruz Morales of Washington DC (US)
Julian Duque of Arlington VA (US)
Kimberly Stockley of Washington DC (US)
MACHINE LEARNING MODEL FOR RECOMMENDING INTERACTION PARTIES
This abstract first appeared for US patent application 18816653 titled 'MACHINE LEARNING MODEL FOR RECOMMENDING INTERACTION PARTIES
Original Abstract Submitted
In some implementations, a system may receive interaction data associated with interactions between a user and subsets of a plurality of interaction parties. The system may store the interaction data and the as historical interaction data associated with historical interactions of the user. The system may provide the historical interaction data as input to a machine learning model, which may be trained using supervised learning and the historical interactions of the user or historical interactions of one or more other users with one or more of the plurality of interaction parties. The system may receive an output, based on applying the machine learning model to the historical interaction data, that may indicate one or more recommended interaction parties based at least in part on one or more factors, wherein the one or more recommended parties may be local entities local to a geographic location associated with the user.