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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效用理论对结构化文档进行排名

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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效用和决策理论的新方法来处理结构化文档。这些方法的应用目的是完善结构单元的第一等级,该结构等级是通过基于贝叶斯网络的信息检索模型生成的。通过将在第一阶段获得的后验概率与检索它们的预期效用相结合,可以在新的排名中对单元进行新的排列。使用莎士比亚结构化集合进行了实验工作,结果表明该新方法的有效性得到了改善。

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