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Operational business intelligence measurement and learning system

机译:运营业务智能度量和学习系统

摘要

An automated method of detecting patterns corresponding to a plurality of real world business measures corresponding to a plurality of business processes, assessing the next instance of such measures and related business attributes, and describing the next best action to optimize business outcomes based upon a plurality of control parameters. The system operates by continuously abstracting input data from a process agnostic data system (PADS) that links real-world things, activities and processes, into a process agnostic measure store (PAMS) configured to accept measures data without limitation as to a specific process or a plurality of processes. The machine self-learning system can then automatically project a business outcome, suggest most relevant attributes that can impact the said outcome, and suggest actions to change such outcome(s).
机译:一种自动方法,用于检测与多个业务流程对应的多个现实世界业务度量对应的模式,评估此类度量的下一个实例以及相关的业务属性,并基于多个变量来描述优化业务结果的下一个最佳操作控制参数。该系统通过连续不断地从流程不可知数据系统(PADS)中抽象输入数据来进行操作,该系统将现实世界中的事物,活动和流程链接到流程不可知度量存储(PAMS)中,该流程不可知度量存储被配置为接受度量数据而不受特定流程或多个过程。然后,机器自学习系统可以自动预测业务结果,建议可能影响所述结果的最相关属性,并建议更改此类结果的操作。

著录项

  • 公开/公告号US10467550B1

    专利类型

  • 公开/公告日2019-11-05

    原文格式PDF

  • 申请/专利权人 OPSVEDA INC.;

    申请/专利号US201715582643

  • 发明设计人 SANJIV GUPTA;ABHISHEK BHOOT;DINESH SOMANI;

    申请日2017-04-29

  • 分类号G06N20;G06F7/02;G06N5/02;G06Q30/06;G06Q30/02;G06F16/22;

  • 国家 US

  • 入库时间 2022-08-21 12:13:58

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