Semantically enhanced term frequency

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Abstract

In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and document terms. Our experiments show that when employed in the standard probabilistic retrieval model BM25, the additional semantic information significantly outperforms the standard term frequency, and also improves the effectiveness when additional query expansion is applied. We further analyze the impact of different lexical semantic resources on the IR effectiveness. © 2010 Springer-Verlag Berlin Heidelberg.

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Müller, C., & Gurevych, I. (2010). Semantically enhanced term frequency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 598–601). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_56

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