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SYSTEMS AND USER INTERFACES FOR HOLISTIC, DATA-DRIVEN INVESTIGATION OF BAD ACTOR BEHAVIOR BASED ON CLUSTERING AND SCORING OF RELATED DATA
SYSTEMS AND USER INTERFACES FOR HOLISTIC, DATA-DRIVEN INVESTIGATION OF BAD ACTOR BEHAVIOR BASED ON CLUSTERING AND SCORING OF RELATED DATA
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机译:基于相关数据的聚类和评分的不良行为者行为的整体数据驱动调查的系统和用户界面
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摘要
Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria, rules, indicators, or scenarios so as to generate scores, reports, alerts, or conclusions that the analyst may quickly and efficiently use to evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a risky trading investigation.
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