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Conversational Problem Determination based on Bipartite Graph

机译:基于二部图的会话问题确定

摘要

A cognitive conversation system that generates effective diagnostic questions is provided. The cognitive conversation system receives a set of currently known symptoms (or currently available answers to diagnostic questions) of a reported problem or fault. The system identifies (i) a set of possible root causes of the reported problem based on the currently known symptoms and (ii) probabilities for the set of possible root causes by using a bipartite graph data structure that links possible symptoms with possible root causes. Upon determining that at least one possible root cause has a probability that is higher than a threshold, the system presents an explanation or solution associated with the at least one possible root cause. Upon determining that none of the possible root causes in the set of possible root causes has a probability higher than the threshold, the system presents a question based on information entropy that is computed based on probabilities of the identified possible root causes.
机译:提供了产生有效诊断问题的认知对话系统。认知对话系统接收所报告的问题或故障的一组当前已知的症状(或诊断问题的当前可用答案)。系统基于当前已知的症状识别(i)报告问题的一组可能的根本原因,以及(ii)通过使用将可能的症状与可能的根本原因相关联的二部图数据结构来确定该组可能的根本原因的概率。在确定至少一个可能的根本原因具有高于阈值的概率时,系统呈现与该至少一个可能的根本原因相关联的解释或解决方案。在确定可能的根本原因集合中所有可能的根本原因都不具有高于阈值的概率时,系统基于信息熵提出问题,该信息熵基于所识别的可能的根本原因的概率来计算。

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