Abstract
Previous works in Information Retrieval show that using pieces of text obtain better results than using the whole document as the basic unit to compare with the user’s query. This kind of IR systems is usually called Passage Retrieval (PR). However, there is not a general agreement about how one should define those pieces of text (also known as passages), in order to obtain an optimum performance. This paper proposes a PR system based on a novel selection of variable size passages. It presents an evaluation that shows better results than a standard IR system and several well-known PR systems.
This paper has been partially supported by the Spanish Government (CICYT) project number TIC2000-0664-C02-02.
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Llopis, F., Ferrández, A., Vicedo, J.L. (2002). Text Segmentation for Efficient Information Retrieval. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2002. Lecture Notes in Computer Science, vol 2276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45715-1_39
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DOI: https://doi.org/10.1007/3-540-45715-1_39
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