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Addressing the Variability of Natural Language Expression in Sentence Similarity with Semantic Structure of the Sentences

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Advances in Knowledge Discovery and Data Mining (PAKDD 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5476))

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Abstract

In this paper, we present a new approach that incorporates semantic structure of sentences, in a form of verb-argument structure, to measure semantic similarity between sentences. The variability of natural language expression makes it difficult for existing text similarity measures to accurately identify semantically similar sentences since sentences conveying the same fact or concept may be composed lexically and syntactically different. Inversely, sentences which are lexically common may not necessarily convey the same meaning. This poses a significant impact on many text mining applications’ performance where sentence-level judgment is involved. The evaluation has shown that, by processing sentence at its semantic level, the performance of similarity measures is significantly improved.

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Authors and Affiliations

  1. College of Information Science and Technology, Drexel Univeristy, Philadelphia, PA 19104, USA

    Palakorn Achananuparp, Xiaohua Hu & Christopher C. Yang

Authors
  1. Palakorn Achananuparp
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  2. Xiaohua Hu
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  3. Christopher C. Yang
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Editor information

Editors and Affiliations

  1. Sirindhorn International Institute of Technology, Thammasat University, 131 Moo 5 Tiwanont Road, 12000, Bangkadi, Muang, Pathumthani, Thailand

    Thanaruk Theeramunkong

  2. Dept. of Computer Engineering, Faculty of Engineering, Chulalongkorn University, 10330, Bangkok, Thailand

    Boonserm Kijsirikul

  3. Faculty of Science & Engineering, York University, 355 Lumbers Building, 4700 Keele Street, M3J 1P3, Toronto, Ontario, Canada

    Nick Cercone

  4. School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, 923-1292, Ishikawa, Japan

    Tu-Bao Ho

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© 2009 Springer-Verlag Berlin Heidelberg

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Achananuparp, P., Hu, X., Yang, C.C. (2009). Addressing the Variability of Natural Language Expression in Sentence Similarity with Semantic Structure of the Sentences. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, TB. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2009. Lecture Notes in Computer Science(), vol 5476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01307-2_52

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  • DOI: https://doi.org/10.1007/978-3-642-01307-2_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01306-5

  • Online ISBN: 978-3-642-01307-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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