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Semantic Similarity Calculation of Short Texts Based on Language Network and Word Semantic Information

  • Conference paper
Advanced Computer Architecture

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 451))

Abstract

We first analyzes the deviation when current similarity calculation methods for texts are applied to short texts, and proposes a similarity calculation method for short texts based on language network and word semantic information. Firstly, models the short texts as language network according to the complex-network characteristic of human being’s language. Then analyzes the comprehensive eigenvalue of the words in the language network and the word similarity between different texts to obtain the word semantic. Calculate the similarity between short texts combining language network and word semantic. Finally the effectiveness of proposed algorithm is verified through clustering algorithm experiments.

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Author information

Authors and Affiliations

  1. School of Information, Renmin University of China, Beijing, 100872, China

    Zhijian Zhan & Xiaoping Yang

  2. School of Opto-electronic and communication Engineering, Xiamen, China

    Feng Lin

Authors
  1. Zhijian Zhan
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  2. Feng Lin
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  3. Xiaoping Yang
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Editor information

Editors and Affiliations

  1. National University of Defense Technology, 410073, Changsha, China

    Junjie Wu

  2. Shanghai Jiao Tong University, 200240, Shanghai, China

    Haibo Chen

  3. College of Information Science and Engineering, Northeastern University Shenyang, China

    Xingwei Wang

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Zhan, Z., Lin, F., Yang, X. (2014). Semantic Similarity Calculation of Short Texts Based on Language Network and Word Semantic Information. In: Wu, J., Chen, H., Wang, X. (eds) Advanced Computer Architecture. Communications in Computer and Information Science, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44491-7_17

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  • DOI: https://doi.org/10.1007/978-3-662-44491-7_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44490-0

  • Online ISBN: 978-3-662-44491-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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