发明名称 System and Method for Analyzing and Predicting Behavior of an Organization and Personnel
摘要 A networked computer system permits users to analyze events associated with a target entity, using primarily externally reported data. By analyzing the target entity's personnel, procedures and reports, embodiments of the invention can assess, present and predict outcomes and timings of submissions processed by the target entity/organization.
申请公布号 US2017039663(A1) 申请公布日期 2017.02.09
申请号 US201615230908 申请日期 2016.08.08
申请人 Gross John Nicholas 发明人 Gross John Nicholas
分类号 G06Q50/18;G06Q10/06 主分类号 G06Q50/18
代理机构 代理人
主权项 1. A method of indirectly analyzing and predicting behavior of a target organization with a computing system, which target organization processes input submissions from third parties using a staff of human personnel in accordance with a first rule set to generate output events, the method comprising: causing the computing system to access a publicly accessible database of event records derived from the output events of the target organization, and which event records identify at least an event type and event date associated with processing by the target organization of the submission; wherein the computing system does not access said event records from databases that are only accessible internally to said target organization through computing systems of such organization; processing the event records with the computing system to identify a historical event behavior of the target organization, including a timing performance parameter and a resolution parameter associated with the events; wherein at least one of a Bayesian model and a Hidden Markov Model is generated and maintained based on analyzing a relationship of individual ones of the output events identified in event records for a plurality of input submissions; generating and reporting on a target prediction of additional events to be generated by the target organization for a first submission based on one or more recent events associated with said first submission and using said Bayesian model and/or Hidden Markov Model.
地址 Berkeley CA US