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METHODS AND SYSTEMS FOR OPTIMIZED POLICY GENERATION TO TRANSFORM COMPUTING ANALYTICS FRAMEWORKS INTO CROSS-PLATFORM REAL-TIME DECISION-MAKING SYSTEMS
METHODS AND SYSTEMS FOR OPTIMIZED POLICY GENERATION TO TRANSFORM COMPUTING ANALYTICS FRAMEWORKS INTO CROSS-PLATFORM REAL-TIME DECISION-MAKING SYSTEMS
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机译：优化策略生成的方法和系统，将分析框架从计算平台转换为跨平台实时决策系统
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摘要
Systems described herein provide structures and functionality for transforming passive analytics systems into systems that can actively modify software behavior based on analytic data to improve software performance relative to configurable goal metrics. An example method generally includes receiving, via a computing network, time-series data collected by a remotely executed software application for a plurality of sessions; storing the time-series data in a persistent data repository; receiving a goal definition specifying how to calculate a goal score based on at least one metric that is calculable based on the time-series data; for each session, determining a value for the at least one metric; based on the time-series data and the values for the sessions, training a machine-learning model to determine, based on events that precede a decision-point event in a session, one or more actions for the remotely executed software application to perform in response to the decision-point event; generating a decision-making policy from the trained machine-learning model; and deploying the policy to a location in the computing network where decision-making requests originating from the software application are received.
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