Abstract
The goal of the paper is to assess the usefulness of various text similarity measures for the two layered Internet search. In that approach the first layer is a generic Internet search engine. The second layer enables the user to evaluate, reorganize, filter and personalize the results of first layer search. It is run on a local work station and can fully exploit the so called user dividend. Crucial for that stage is assessing text similarity between text segments. The papers discusses classical, statistic text similarity measures as well semantic, WordNet based semantic measures. The results of an experiment show, that without word disambiguation techniques the semantic approaches can not outperform statistic methods.
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Siemiński, A. (2010). Verifying Text Similarity Measures for Two Layered Retrieval. In: Nguyen, N.T., Zgrzywa, A., Czyżewski, A. (eds) Advances in Multimedia and Network Information System Technologies. Advances in Intelligent and Soft Computing, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14989-4_23
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DOI: https://doi.org/10.1007/978-3-642-14989-4_23
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