Invention Grant
- Patent Title: Machine learning models for evaluating entities in a high-volume computer network
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Application No.: US15618406Application Date: 2017-06-09
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Publication No.: US10853739B2Publication Date: 2020-12-01
- Inventor: Tu Truong , Fuming Wu , Julio Navas , Ajain Kuzhimattathil , Hanxiang Chen , Nazanin Zaker Habibabadi , Omar Rahman , Han Li
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/08 ; G06N3/04 ; G06F3/0481 ; G06N5/00 ; G06N20/10 ; G06N7/00
Abstract:
In an example, a machine learning algorithm is used to train an entity risk evaluation model to output an entity risk score based on transaction data in a computer network. Entity risk scores for various entities may be stored in a database, and retrieved and displayed upon user interaction with one or more reports involving corresponding entities.
Public/Granted literature
- US20180357559A1 MACHINE LEARNING MODELS FOR EVALUATING ENTITIES IN A HIGH-VOLUME COMPUTER NETWORK Public/Granted day:2018-12-13
Information query
