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The Effectiveness of Automatically Structured Queries in Digital Libraries ABSTRACT
BibTeX
@MISC{André_theeffectiveness,
author = {Marcos André and Gonçalves Edward and A. Fox and Aaron Krowne and Pável Calado and Alberto H. F. Laender and Altigran S. Silva and Berthier Ribeiro-neto},
title = {The Effectiveness of Automatically Structured Queries in Digital Libraries ABSTRACT},
year = {}
}
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Abstract
Structured or fielded metadata is the basis for many digital library services, including searching and browsing. Yet, little is known about the impact of using structure on the effectiveness of such services. In this paper, we investigate a key research question: do structured queries improve effectiveness in DL searching? To answer this question, we empirically compared the use of unstructured queries to the use of structured queries. We then tested the capability of a simple Bayesian network system, built on top of a DL retrieval engine, to infer the best structured queries from the keywords entered by the user. Experiments performed with 20 subjects working with a DL containing a large collection of computer science literature clearly indicate that structured queries, either manually constructed or automatically generated, perform better than their unstructured counterparts, in the majority of cases. Also, automatic structuring of queries appears to be an effective and viable alternative to manual structuring that may significantly reduce the burden on users.
Keyphrases
structured query digital library abstract automatically structured query many digital library service large collection key research question automatic structuring viable alternative unstructured query unstructured counterpart simple bayesian network system dl retrieval engine computer science literature
