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.
Chapter PDF
Similar content being viewed by others
References
S. Abiteboul, D. Quass, J. McHugh, J. Widom, and J. Wiener. The lorel query langauge for semistructured data. International Journal of Digital Libraries, 1(1):68–88, 1997.
R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley, 1999.
F. J. Burkowski. An algebra for hierarchically organized text-dominated databases. Information Processing & Management, 28(3):333–348, 1992.
C. L. A. Clarke, G. V. Cormack, and F. J. Burkowski. An algebra for structured text search and a framework for its implementation. The Computer Journal, 38(1):43–56, 1995.
M. Fernández, P. Pavón, J. Rodríguez, L. Anido, and M. Llamas. Delfosnetx: A workbench for XML-based information retrieval systems. In Procs. of the 7th International Symposium of String Processing and Information Retrieval, pages 87–95. IEEE Comp. Soc. Press, 2000.
A. L. Hors, P. L. Hégaret, L. Wood, G. Nicol, J. Robie, M. Champion, and S. Byrne, editors. Document Object Model Level 2 Core Specification. W3 Consortium, 1998. W3C Recommendation.
G. Salton and M. E. Lesk. Computer evaluation of indexing and text processing. Journal of the ACM, 15(1):8–36, 1968.
H. Schneider and G. P. Barker. Matrices and Linear Algebra. Dover Books on Advanced Mathematics. Dover Pubns, 2nd edition, 1989.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fernández-Iglesias, M.J., Rodríguez, J.S., Anido, L., Santos, J., Caeiro, M., Llamas, M. (2002). Modeling Metadata-Enabled Information Retrieval. In: Sloot, P.M.A., Hoekstra, A.G., Tan, C.J.K., Dongarra, J.J. (eds) Computational Science — ICCS 2002. ICCS 2002. Lecture Notes in Computer Science, vol 2329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46043-8_7
Download citation
DOI: https://doi.org/10.1007/3-540-46043-8_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43591-4
Online ISBN: 978-3-540-46043-5
eBook Packages: Springer Book Archive