Invention Grant
- Patent Title: Multi-task deep learning of customer demand
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Application No.: US16675314Application Date: 2019-11-06
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Publication No.: US11966927B2Publication Date: 2024-04-23
- Inventor: Min Xiao
- Applicant: ADP, Inc.
- Applicant Address: US NJ Roseland
- Assignee: ADP, Inc.
- Current Assignee: ADP, Inc.
- Current Assignee Address: US NJ Roseland
- Agency: Foley & Lardner LLP
- Main IPC: G06Q30/016
- IPC: G06Q30/016 ; G06N3/044 ; G06N3/08

Abstract:
A method for predicting changes in customer demand is provided. The method comprises collecting subscription data for a number of customers at specified time intervals, wherein each customer is subscribed to one of a number of defined bundles of services. Any changes in customer bundle subscriptions during a given time interval are determined along with metrics for defined customer tasks for subscribed services during the given time interval. Multimodal multi-task learning is used to simultaneously model both bundle subscription change events and time-to-event for each bundle subscription change. Using the modeling, types and timing of changes in customer bundle subscriptions are predicted based on customer service activities.
Public/Granted literature
- US20210133766A1 Multi-Task Deep Learning of Client Demand Public/Granted day:2021-05-06
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