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    • 1. 发明申请
    • SYSTEM AND METHOD FOR CORRELATING PAST ACTIVITIES, DETERMINING HIDDEN RELATIONSHIPS AND PREDICTING FUTURE ACTIVITIES
    • 用于相关活动的系统和方法,确定隐藏关系和预测未来活动
    • WO2011014471A1
    • 2011-02-03
    • PCT/US2010/043301
    • 2010-07-27
    • SENSIS CORPORATIONKUECUEKYAN, Horen
    • KUECUEKYAN, Horen
    • G06F7/00
    • G06N99/005
    • A system and method of data correlation and analysis of past activities and prediction of future activity that includes establishing a database comprising structured metadata on at least one computer and a distributed system of networked computers having a plurality of access levels, configuring a database front-end to parse incoming data, the database front-end defining a plurality of entities and events, each having one or more attributes, and correlation IDs, which are user defined attribute relationships that correlate events and entities, collecting data, parsing the incoming data in the database front-end into structured metadata, the distributed analysis engine correlating the incoming structured metadata with structured metadata in the database and determining micro-patterns in the structured metadata, generating a graphical representation of a composite network of the determined micro-patterns as super-objects, and predicting future activity from the one or more super-objects representing the determined micro-patterns.
    • 数据相关和分析过去活动和对未来活动的预测的系统和方法,其包括在至少一台计算机上建立包括结构化元数据的数据库和具有多个访问级别的联网计算机的分布式系统,配置数据库前端 解析输入数据,数据库前端定义多个具有一个或多个属性的实体和事件,以及相关性ID,这些用户定义的属性关系将事件和实体相关联,收集数据,解析输入数据中的输入数据 数据库前端成为结构化元数据,分布式分析引擎将输入的结构化元数据与数据库中的结构化元数据相关联,并确定结构化元数据中的微模式,生成所确定的微模式的复合网络的图形表示, 对象,并从一个或多个超对象预测未来活动 代表确定的微观模式。