Modeling Metadata-Enabled Information Retrieval

  • Authors:
  • Manuel J. Fernández Iglesias;Judith S. Rodríguez;Luis E. Anido-Rifón;Juan M. Santos;Manuel Caeiro;Martín Llamas Nistal

  • Affiliations:
  • -;-;-;-;-;-

  • Venue:
  • ICCS '02 Proceedings of the International Conference on Computational Science-Part I
  • Year:
  • 2002

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Abstract

We introduce a proposal to theoretically characterize Information Retrieval (IR) supporting metadata. The proposed model has its foundation in a classical approach to IR, namely vector models. These models are simple and implementations are fast, their term-weighting approach improve retrieval performance, allow partial matching, and support document ranking. The proposed characterization includes document and query representations, support for typical IR-related activities like stemming, stoplist application or dictionary transformations, and a framework for similarity calculation and document ranking. The classical vector model is integrated as a particular case in the new proposal.