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Sentence Similarity on Structural Representations

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10102))

Abstract

Most previous approaches used various kinds of plain similarity features to represent the similarity of a sentence pair, and one of its limitations is its weak representation ability. This paper introduces the relational structures representation (shallow syntactic tree, dependency tree) to compute sentence similarity. Experimental results manifest that our approach achieves higher performance than that only uses plain features.

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Correspondence to Peifeng Li .

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© 2016 Springer International Publishing AG

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Yang, M., Li, P., Zhu, Q. (2016). Sentence Similarity on Structural Representations. In: Lin, CY., Xue, N., Zhao, D., Huang, X., Feng, Y. (eds) Natural Language Understanding and Intelligent Applications. ICCPOL NLPCC 2016 2016. Lecture Notes in Computer Science(), vol 10102. Springer, Cham. https://doi.org/10.1007/978-3-319-50496-4_40

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  • DOI: https://doi.org/10.1007/978-3-319-50496-4_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50495-7

  • Online ISBN: 978-3-319-50496-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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