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The Design of Philosophy and Social Sciences Terms Dictionary System Based on Big Data Mining

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Advanced Hybrid Information Processing (ADHIP 2020)

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Abstract

Aiming at the problem that the traditional dictionary system cannot use the big data mining technology for term calculation, which leads to the long response time of the dictionary system retrieval, a philosophy and social science term dictionary system based on big data mining is designed. The hardware part designs the system controller and connects the single-chip microcomputer connection circuit. The software part first divides the term dimensions according to the characteristics of philosophy and social science terms, mines the corpus according to different dimensions, completes the calculation of philosophy and social science terms, sets up the term database structure, and finally completes the software design of the dictionary system. The experimental results show that: Compared with the traditional dictionary system, the search time of philosophy and Social Sciences terminology dictionary system based on big data mining is the shortest, and the detection accuracy of philosophy and social science terms is higher, which is suitable for all applications.

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Authors and Affiliations

  1. School of Humanities, Tongji University, Shanghai, 200092, China

    Han-yang Li

  2. School of Journalism and Communication, Minnan Normal University, Zhangzhou, 363000, China

    Han-yang Li

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  1. Han-yang Li
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Correspondence to Han-yang Li .

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Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Shuai Liu

  2. Hunan Normal University, Changsha, China

    Liyun Xia

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, Hy. (2021). The Design of Philosophy and Social Sciences Terms Dictionary System Based on Big Data Mining. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-030-67871-5_14

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  • DOI: https://doi.org/10.1007/978-3-030-67871-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67870-8

  • Online ISBN: 978-3-030-67871-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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