DEXA 1997: Database and Expert Systems Applications pp 214-224 | Cite as
An image retrieval system based on the visualization of system relevance via documents
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Abstract
This paper describes a system for an image retrieval system in which relevance related and system-use related user strategies can be performed. The query supports, in addition to classical topical inputs, strategic parameters that can be set by the user, either directly or via the visualization of retrieved images that are organized with respect to which relevance criteria are verified. Typical retrieval situations are defined, that account for the dynamic aspect of a given retrieval session.
Keywords
Elementary Criterion Relevance Criterion Information Retrieval System Relevance Judgment Image Retrieval System
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
- 1.M. E. Adiba and C. Collet. Objets et bases de données, le SGBD O2. Hermès, 1993.Google Scholar
- 2.C.L. Barry. User-defined relevance criteria: an exploratory study. Journal of the American Society for Information Science, 45(3):135–141, 1994.Google Scholar
- 3.W.B. Croft and R.H. Thompson. The use of adaptive mechanisms for selection of search strategies in document retrieval systems. In Third Joint BCS-ACM Symposium, Cambridge, 1984.Google Scholar
- 4.N. Denos. Modelling relevance in information retrieval systems: a conceptual model based on user criteria for relevance, and a formalization. Rapport de recherche, CLIPS-IMAG, 1997.Google Scholar
- 5.N. Denos. Modéliser la pertinence pour l'utilisateur d'un système de recherche d'information: modèle conceptuel, formalisation et application. PhD thesis, Université Joseph Fourier Grenoble I, 1997. Forthcoming.Google Scholar
- 6.C.J. van Rijsbergen. Information Retrieval. Butterworths, second edition, 1979.Google Scholar
- 7.J.J. Rocchio Jr. Relevance feedback in information retrieval. In G. Salton, editor, The SMART retrieval System-Experiments in Automatic Document Processing, chapter 14, pages 313–323. Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1971.Google Scholar
- 8.Gerard Salton and M.J. McGill. Introduction to modern Information Retrieval. Mcgraw Hill Book Company, New York, 1983.Google Scholar
- 9.L. Schamber. Annual review of information science and technology — volume 29, chapter 1. Learned Information, Medford, N.J., 1994.Google Scholar
- 10.M. Smail. Raisonnement à base de cas pour une recherche évolutive d'informations prototype Cabrin — Vers la définition d'un cadre d'acquisition des connaissances. PhD thesis, Université Henri Poincaré, Nancy, France, 1994.Google Scholar
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© Springer-Verlag Berlin Heidelberg 1997