Invention Grant
- Patent Title: Machine-learning system for clickstream-based content interest prediction
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Application No.: US17085571Application Date: 2020-10-30
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Publication No.: US12165170B2Publication Date: 2024-12-10
- Inventor: Tajdar Shameem Siddiqui , Stephen Filios , Michelle Schroeder , Logan Sommers Ahlstrom
- Applicant: TD Ameritrade IP Company, Inc.
- Applicant Address: US NE Omaha
- Assignee: TD Ameritrade IP Company, Inc.
- Current Assignee: TD Ameritrade IP Company, Inc.
- Current Assignee Address: US NE Omaha
- Agency: Harness, Dickey & Pierce, P.L.C.
- Main IPC: G06Q30/0242
- IPC: G06Q30/0242 ; G06F18/2415 ; G06N5/046 ; G06N20/00

Abstract:
A method includes receiving client data of a client that includes at least one of clickstream data and analytic data of the client. For each of a number of trained machine learning (ML) models corresponding, respectively, to a number of campaigns, campaign-specific features are extracted from the client data, and a campaign interest prediction score is generated by inputting the campaign-specific features extracted for the ML model into the ML model. At least one campaign, from among the plurality of campaigns, is assigned to the client based on the generated campaign interest prediction scores. The clickstream data includes a plurality of pages visited by the client, and the analytic data of the client includes at least one of phone call data, chat message data, email data, or survey data of the client.
Public/Granted literature
- US20220138795A1 Machine-Learning System for Clickstream-Based Content Interest Prediction Public/Granted day:2022-05-05
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