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Ranking Structured Documents Using Utility Theory in the Bayesian Network Retrieval Model

机译:在贝叶斯网络检索模型中使用实用工具理论排名结构化文件

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In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the first stage, with the expected utility of retrieving them. The experimental work has been developed using the Shakespeare structured collection and the results show an improvement of the effectiveness of this new approach.
机译:本文提出了一种基于实用程序和决策理论的新方法来处理结构化文件。这些方法的应用的目的是通过基于贝叶斯网络的信息检索模型来改进结构单元的第一排名。通过组合在第一阶段获得的后验概率来新排名的单位在新排名中,预期的检索它们的效用。使用莎士比亚结构集合开发了实验工作,结果表明了这种新方法的有效性的提高。

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