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2018 , Vol. 62 >Issue 21: 118 - 126

DOI: https://doi.org/10.13266/j.issn.0252-3116.2018.21.015

Patent Topic Discovery Method Integrated with Term Knowledge

  • Yu Yan ,
  • Zhao Naixuan
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  • 1. Information Service Department, Nanjing Tech University, Nanjing 210009;
    2. Computer Science Department, Southeast University Chengxian College, Nanjing 211816

Received date: 2018-04-07

  Revised date: 2018-06-20

  Online published: 2018-11-05

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Abstract

[Purpose/significance] Aiming at the problem of analysis patent topic in terms of word which causes topics are difficult to explain in the patent topic analysis, this paper proposes a patent topic discovery model integrated with term knowledge.[Method/process]The proposed model firstly introduces the class entropy and effectively recognizes the terms in the patent literature. Then, the Generalized Pólya Urn model is used to increase the probability of the semantic similarity terms assigned to the same topic, in order to alleviate the data sparsity problem brought by the term as the basic topic model analysis unit.[Result/conclusion]The experimental results show that the proposed model contains the term information to improve the quality of the topic generation, making the topic representation more readable and topic discriminative.

Key words： patent analysis; topic discovery; term

Cite this article

Yu Yan , Zhao Naixuan . Patent Topic Discovery Method Integrated with Term Knowledge[J]. Library and Information Service, 2018 , 62(21) : 118 -126 . DOI: 10.13266/j.issn.0252-3116.2018.21.015

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