A relevance model for a data warehouse contextualized with documents

Authors:
Juan Manuel Pérez;Rafael Berlanga;María José Aramburu
Affiliations:
Universitat Jaume I, Campus de Riu Sec, E-12071 Castelló de la Plana, Spain;Universitat Jaume I, Campus de Riu Sec, E-12071 Castelló de la Plana, Spain;Universitat Jaume I, Campus de Riu Sec, E-12071 Castelló de la Plana, Spain
Venue:
Information Processing and Management: an International Journal
Year:
2009

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Abstract

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.