Abstract
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. © Springer-Verlag Berlin Heidelberg 2003.
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CITATION STYLE
Crestani, F., De Campos, L. M., Fernández-Luna, J. M., & Huete, J. F. (2003). Ranking structured documents using utility theory in the Bayesian Network Retrieval Model. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2857, 168–182. https://doi.org/10.1007/978-3-540-39984-1_13
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