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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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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