Abstract
The present work aims at refining and expanding user’s queries thanks to association rules. We adapted the A-Close algorithm to a medical corpus indexed by MeSH descriptors. The originality of our approach lies in the use of the association rules in the information retrieval process and the exploitation of the structure of the domain knowledge to evaluate the association rules. The results show the usefulness of this query expansion approach. Based on observations, new knowledge is modelled as expert rules.
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References
Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules in Large Databases. In: VLDB, pp. 478–499 (1994)
Pasquier, N., et al.: Generating a Condensed Representation of Association Rules. Intelligent information systems (2004)
Soualmia, L.F., Darmoni, S.J.: Combining Knowledge-based Methods to Refine and Expand Queries in Medicine. In: Christiansen, H., Hacid, M.-S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2004. LNCS (LNAI), vol. 3055, pp. 243–255. Springer, Heidelberg (2004)
Fayyad, U.M., et al.: Advances in Knowledge Discovery and Data Mining. AAAI Press, Stanford (1996)
Névéol, A., et al.: Using MeSH Encapsulated Terminology and a Categorization Algorithm for Health Resources. International Journal of Medical Informatics 73(1), 57–64 (2004)
Magennis, M., Van Rijsbergen, C.J.: The Potential and Actual Effectiveness of Interactive Query Expansion. In: SIGIR, pp. 324–332 (1997)
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© 2007 Springer-Verlag Berlin Heidelberg
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Soualmia, L.F., Dahamna, B. (2007). Knowledge Acquisition from a Medical Corpus: Use and Return on Experiences. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_19
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DOI: https://doi.org/10.1007/978-3-540-73599-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73598-4
Online ISBN: 978-3-540-73599-1
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