Ranking structured documents using utility theory in the Bayesian network retrieval model

Fabio Crestani; Luis M. de Campos; Juan M. Fernandez Luna; Juan F. Huete

Ranking structured documents using utility theory in the Bayesian network retrieval model

Fabio Crestani, Luis M. de Campos, Juan M. Fernandez Luna, Juan F. Huete

Computer And Information Sciences

Research output: Contribution to conference › Paper › peer-review

11 Citations (Scopus)

48 Downloads (Pure)

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.

Original language	English
Pages	168-182
Number of pages	14
Publication status	Published - 10 Oct 2003
Event	Proceedings of the SPIRE 2003 - Manaus, Brasil Duration: 8 Oct 2003 → 19 Oct 2003

Conference

Conference	Proceedings of the SPIRE 2003
City	Manaus, Brasil
Period	8/10/03 → 19/10/03

Keywords

utility theory
Bayesian network retrieval model
information retreival

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strathprints002496Accepted author manuscript, 222 KB

Cite this

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title = "Ranking structured documents using utility theory in the Bayesian network retrieval model",

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.",

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AU - Crestani, Fabio

AU - de Campos, Luis M.

AU - Fernandez Luna, Juan M.

AU - Huete, Juan F.

PY - 2003/10/10

Y1 - 2003/10/10

N2 - 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.

AB - 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.

KW - utility theory

KW - Bayesian network retrieval model

KW - information retreival

M3 - Paper

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EP - 182

T2 - Proceedings of the SPIRE 2003

Y2 - 8 October 2003 through 19 October 2003

ER -

Ranking structured documents using utility theory in the Bayesian network retrieval model

Abstract

Conference

Keywords

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