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    • 3. 发明公开
    • SYSTEMS AND USER INTERFACES FOR HOLISTIC, DATA-DRIVEN INVESTIGATION OF BAD ACTOR BEHAVIOR BASED ON CLUSTERING AND SCORING OF RELATED DATA
    • 系统和用户界面坏人行为的综合数据对照研究基于组群及相关数据的评估
    • EP3125186A1
    • 2017-02-01
    • EP16181945.3
    • 2016-07-29
    • Palantir Technologies, Inc.
    • Hunter, SeanKumar, AdityaAlbertson, Jacob
    • G06Q40/00
    • G06Q40/04G06F3/0482G06F17/30522G06F17/30598G06Q40/00
    • 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.
    • 本公开的实施例涉及一种数据分析系统也可以自动生成存储器高效的聚类的数据结构,自动地分析这些聚类的数据结构,自动标记和组这些聚类的数据结构,并提供自动化分析的结果,并在优化分组在 办法分析师。 群集的数据结构的自动分析(由作为数据群集进入简称)可以包括在各种标准,规则,指示器或场景自动应用程序,以产生评分,报告,警报,或结论做了分析员可以迅速和 有效地使用评估数据簇群。 特别是,数据的簇的基团可以被动态地重新分组和/或在给交互式用户界面过滤以使分析师之间与数据群集的各个组相关联的信息来快速导航,并在上下文有效地评估这些数据群集 ,例如,有风险的交易调查。