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China Conference on Knowledge Graph and Semantic Computing

CCKS 2018: Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding pp 116–128Cite as

Predicting Concept-Based Research Trends with Rhetorical Framing

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 957))

Abstract

Applying data mining techniques to help researchers discover, understand, and predict research trends is a highly beneficial but challenging task. The existing researches mainly use topics extracted from literatures as objects to build predicting model. To get more accurate results, we use concepts instead of topics constructing a model to predict their rise and fall trends, considering the rhetorical characteristics of them. The experimental results based on ACL1965-2017 literature dataset show the clues of the scientific trends can be found in the rhetorical distribution of concepts. After adding the relevant concepts’ information, the predict model’s accuracy rate can be significantly improved, compared to the prior topic-based algorithm.

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Acknowledgement

The work is supported by National Key Research and Development Program of China (2017YFB1002101), NSFC key project (U1736204, 61661146007) and THUNUS NExT Co-Lab.

Author information

Authors and Affiliations

  1. Tsinghua University, Beijing, China

    Jifan Yu & Juanzi Li

  2. National University of Singapore, Singapore, Singapore

    Liangming Pan

  3. Beihang University, Beijing, China

    Xiaoping Du

Authors
  1. Jifan Yu
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  2. Liangming Pan
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  3. Juanzi Li
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  4. Xiaoping Du
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Corresponding author

Correspondence to Jifan Yu .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Jun Zhao

  2. Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Frank van Harmelen

  3. Tsinghua University, Beijing, China

    Jie Tang

  4. Institute of Software, Chinese Academy of Sciences, Beijing, China

    Xianpei Han

  5. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Quan Wang

  6. Xihua University, Chendu, China

    Xianyong Li

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© 2019 Springer Nature Singapore Pte Ltd.

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Yu, J., Pan, L., Li, J., Du, X. (2019). Predicting Concept-Based Research Trends with Rhetorical Framing. In: Zhao, J., Harmelen, F., Tang, J., Han, X., Wang, Q., Li, X. (eds) Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding. CCKS 2018. Communications in Computer and Information Science, vol 957. Springer, Singapore. https://doi.org/10.1007/978-981-13-3146-6_10

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  • DOI: https://doi.org/10.1007/978-981-13-3146-6_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3145-9

  • Online ISBN: 978-981-13-3146-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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