Invention Grant
- Patent Title: System and method for unsupervised abstraction of sensitive data for detection model sharing across entities
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Application No.: US16674467Application Date: 2019-11-05
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Publication No.: US12056720B2Publication Date: 2024-08-06
- Inventor: Brandon Harris , Eugene I. Kelton , Chaz Vollmer
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Kelsey M. Skodje
- Main IPC: G06Q30/0201
- IPC: G06Q30/0201 ; G06F18/21 ; G06F18/211 ; G06F18/23211 ; G06N3/088 ; G06Q30/0202 ; G06Q30/0204

Abstract:
An abstraction system for generating a standard customer profile may receive customer data and perform unsupervised learning on the customer data to produce a plurality of clusters of customers with a plurality of features in common, determine that a cluster represents a standard customer and store a plurality of standard customer profiles based on the determined standard customers. The abstraction system may also provide the standard customer profiles to a cognitive system for generating synthetic transaction data based on the standard customer. Generating synthetic transaction data includes selecting a standard customer profile as a goal, simulating a plurality of transactions, comparing the plurality of transactions with the goal, providing feedback, adjusting a policy based on the feedback, repeating until a degree of similarity between the plurality of transactions and the goal is higher than a predefined threshold, and outputting the resulting plurality of transactions as the synthetic transaction data.
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