A relevance model for a data warehouse contextualized with documents
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Scholar |
Otros documentos de la autoría: Pérez Martínez, Juan Manuel; Berlanga Llavori, Rafael; Aramburu Cabo, María José
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/8634
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http://dx.doi.org/10.1016/j.ipm.2008.11.001 |
Metadatos
Título
A relevance model for a data warehouse contextualized with documentsFecha de publicación
2009Editor
ElsevierISSN
3064573Cita bibliográfica
Information Processing and Management, 45, 3, p. 356-367Tipo de documento
info:eu-repo/semantics/articlePalabras clave / Materias
Resumen
This paper presents a relevance model to rank the facts of a data warehouse that are described in a set of documents retrieved with an information retrieval (IR) query. The model is based in language modeling and ... [+]
This paper presents a relevance model to rank the facts of a data warehouse that are described in a set of documents retrieved with an information retrieval (IR) query. The model is based in language modeling and relevance modeling techniques. We estimate the relevance of the facts by the probability of finding their dimensions values and the query keywords in the documents that are relevant to the query. The model is the core of the so-called contextualized warehouse, which is a new kind of decision support system that combines structured data sources and document collections. The paper evaluates the relevance model with the Wall Street Journal (WSJ) TREC test subcollection and a self-constructed fact database. © 2008 Elsevier Ltd. All rights reserved. [-]
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info:eu-repo/semantics/restrictedAccess
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