Abstract
Similar sentence extraction is an important issue because it is the basis of many applications. In this paper, we conduct comprehensive experiments on evaluating the performance of similar sentence extraction in a general framework. The effectiveness and the efficiency issues are explored on three real datasets, with different factors considered, i.e., size of data, top-k value. Moreover, the WordNet is taken into account as an additional semantic resource and incorporated into the framework. We thoroughly explore the performance of the updated framework to study the similar sentence extraction. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Gu, Y., Yang, Z., Nakano, M., & Kitsuregawa, M. (2013). Performance evaluation of similar sentences extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7813 LNCS, pp. 86–94). Springer Verlag. https://doi.org/10.1007/978-3-642-37134-9_7
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