间接言语行为理论的贝叶斯信念网络模型

Xianbo Li, Huanrun Qiao, Zhicheng Ma, Diaodiao Yang, Yongtai Pan, Zhixin Ma
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引用次数: 2

摘要

朴素贝叶斯概率模型应用于理性言语行为和不确定理性言语行为。所有的定语必须有条件地相互独立,这一要求对于间接言语行为来说过于严格,因为定语不一定满足话语中独立的阶级条件的假设。因此,本文提出了间接言语行为理论的贝叶斯信念网络模型来消除独立条件。利用认知模型理论和非参数估计方法构建说话人对真实世界的认知属性和对说话人行为的判断属性,实现间接言语行为中的言外行为和言外行为。构造条件概率表,使模型更加客观实用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian Belief Network Model of Indirect Speech Act Theory
Naive Bayesian probability model has been employed in rational speech act and uncertain rational speech act. The requirement, all attributes must be conditionally independent of each other, is too strict for indirect speech act because the attributes do not necessarily satisfy the assumption of independent class conditions in discourse. Therefore, a Bayesian belief network model of indirect speech act theory is proposed to cancel the independent conditions. Cognitive model theory and non-parametric estimation methods are used to construct the cognitive attributes for the real world and the judgment attributes of the speaker's behavior to achieve the illocutionary act and perlocutionary act in the indirect speech act. The conditional probability table is constructed to make the model more objective and practical.
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