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Generating state predictive metrics based on Markov chain model from application operational state sequences
Generating state predictive metrics based on Markov chain model from application operational state sequences
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机译：从应用程序操作状态序列中基于Markov链模型生成状态预测指标
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摘要
An application analysis computer obtains reports from user terminals identifying operational states of instances of an application being processed by the user terminals. Sequences of the operational states that the instances of the application have transitioned through while being processed by the user terminals are identified. Common operational states that occur in a plurality of the sequences are identified. For each of the common operational states, a frequency of occurrence of the common operational state is determined. For each state transition between the common operational states in the sequences, a frequency of occurrence of the state transition is determined. State predictive metrics are generated based on the frequencies of occurrence of the common operational states and the frequencies of occurrence of the state transitions. The state predictive metrics are communicated, such as to an application server to control access to the application by user terminals.
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