Abstract
In a Relevance Feedback process, the query can be reformulated basing on a matrix product of the RSV (Retrieval Status Value) vector and the documents-terms matrix. In such case, the challenge is to determine the most appropriate query that fulfils the retrieval process. In this paper, we present an automatic query reformulation approach based on a dual form of this product matrix which systematically generate as solution the reformulated query. This approach was spread to assure a learning strategy in order to rank the results of an information retrieval system. Some experiments have been undertaken into a dataset provided by TREC and the results show the effectiveness of our approach.
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References
Buckley, S.-G., Allan, C.J.: Automatic retrieval with locality information using smart. In: The First Text REtrieval Conference (TREC-1), pp. 59–72. National Institute of Standards and Technology, Gaithersburg (1992)
Campos, L.M.D., Huete, J.F., Fernndez-Luna, J.M., Spain, J.: Document instantiation for relevance feedback in the bayesian network retrieval model (2001)
Efthimiadis, E.: Interactive query expansion: a user based evaluation in relevance feedback environment. Journal of the American Society for Information Science 51(11), 989–1003 (2000)
Efthimiadis, N.E.: Query expansion. In Annual Review of Information Systems and Technology 31, 121–187 (1996)
Salton, G.: The SMART Retrieval System – Experiments in Automatic Document Processing. Prentice Hall, Englewood Cliffs (1971)
Salton, G., McGill, M.: Introduction to Modern Information Retrieval. McGraw-Hill, New York (1984)
Rocchio, J.J.: Relevance feedback in information retrieval. In: The SMART Retrieval System – Experiments in Automatic Document Processing [5], pp. 313–323
Robertson, S., Sparck-Jones, J.K.: Relevance weighting of search terms. Journal of the American Siciety for Information Science 27(3), 129–146 (1976)
Ruthven, I., Lalmas, M.: A survey on the use of relevance feedback for information access systems. Knowl. Eng. Rev. 18(2), 95–145 (2003)
Johnson, S.C.: Hierarchical clustering schemes, vol. 32, pp. 241–254 (1967)
van Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworths, London (1979)
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© 2009 Springer-Verlag Berlin Heidelberg
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Taktak, I., Tmar, M., Hamadou, A.B. (2009). Query Reformulation Based on Relevance Feedback. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_12
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DOI: https://doi.org/10.1007/978-3-642-04957-6_12
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