Jpmorgan Chase Bank, N.a.

Liang Zhou

Howard Spector

Somnath Choudhuri

Neil O'Donnell

Timothy Lorenz

Prashant K Dhingra

Eric-Andre Vigroux

Riti Singhal

Rebecca Setting

Song Ting Ceng

Akshay Karnawat

Jiangling Wang

James Kaczmarczyk

Christopher J Leasor

Yihui Tang

Hong Ji

Rakesh Pathak

Ramin Koch

Parambir S Mudhar

Mathieu Cliche

Shailender Singh

Various methods, apparatuses/systems, and media for implementing a payment application module for searching billets are disclosed. A plurality of data sources include customer profile data, customer payment history data, biller information data, and biller directory data. A processor operatively coupled to the plurality of data sources via a communication network builds a customer profile service area popularity model based on the customer profile data, customer payment history data, biller information data, and biller directory data; receives search query data for searching a biller; builds a biller search machine learning model to optimize weights applied to the search query data; and ranks search results by utilizing the machine learning model in response to the search query data.

System and method for searching billers with service area popularity model and machine learning

A method for facilitating predictive caching of data is provided. The method includes retrieving raw data relating to user activity for a plurality of users, the user activity including a history of web resources accessed by a user; converting the raw data into a structured data set based on a predetermined criterion; generating a model based on the structured data set; training the model by using a training data set, the training data set including the user activity for a predetermined period of time; determining, by using the trained model, a predicted first web resource for the user; and automatically caching, in a memory, the predicted first web resource.

Method and system for predictively caching data

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New York, NY, United States of America

Liang Zhou