Abstract
With the exponential growth of information on the Internet and the significant increase in the number of pages published each day have led to the emergence of new words in the Internet. Owning to the difficulty of achieving the meaning of these new terms, it becomes important to give more weight to subjects and sites where these new words appear, or rather, to give value to the words that occur frequently with them. For this reason, in this work, we propose an effective term-ranking function for query expansion based on the co-occurrence and proximity of words for retrieval effectiveness enhancement. A novel efficiency/effectiveness measure based on the principle of optimal information forager is also proposed in order to evaluate the quality of the obtained results. Our experiments were conducted using the OHSUMED test collection and show significant performance improvement over the state-of-the-art.
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Khennak, I., Drias, H., Mosteghanemi, H. (2014). An Effective Term-Ranking Function for Query Expansion Based on Information Foraging Assessment. In: Prasath, R., O’Reilly, P., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8891. Springer, Cham. https://doi.org/10.1007/978-3-319-13817-6_1
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DOI: https://doi.org/10.1007/978-3-319-13817-6_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13816-9
Online ISBN: 978-3-319-13817-6
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