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Transactions on Rough Sets XIV pp 1–17Cite as

Evaluating a Temporal Pattern Detection Method for Finding Research Keys in Bibliographical Data

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Part of the book series: Lecture Notes in Computer Science ((TRS,volume 6600))

Abstract

According to the accumulation of the electrically stored documents, acquisition of valuable knowledge with remarkable trends of technical terms has drawn the attentions as the topic in text mining. In order to support for discovering key topics appeared as key terms in such temporal textual datasets, we propose a method based on temporal patterns in several data-driven indices for text mining. The method consists of an automatic term extraction method in given documents, three importance indices, temporal pattern extraction by using temporal clustering, and trend detection based on linear trends of their centroids. Empirical studies show that the three importance indices are applied to the titles of two academic conferences about artificial intelligence field as the sets of documents. After extracting the temporal patterns of automatically extracted terms, we discuss the trends of the terms including the recent burst words among the titles of the conferences.

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Author information

Authors and Affiliations

  1. Department of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho, Izumo, Shimane, 693-8501, Japan

    Hidenao Abe & Shusaku Tsumoto

Authors
  1. Hidenao Abe
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  2. Shusaku Tsumoto
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Editor information

Editors and Affiliations

  1. University of Manitoba, R3T 5V6, Winnipeg, MB, Canada

    James F. Peters

  2. University of Warsaw, 02-097, Warsaw, Poland

    Andrzej Skowron  & Dominik Slezak  & 

  3. Kyushu Institute of Technology, 804, Tobata, Kitakyushu, Japan

    Hiroshi Sakai

  4. Jadavpur University, Kolkata, Indian Statistical Institute, Kolkata, India

    Mihir Kumar Chakraborty

  5. Cairo University, Orman, Giza, Egypt

    Aboul Ella Hassanien

  6. Zhangzhou Normal University, Fujian, China

    William Zhu

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© 2011 Springer-Verlag Berlin Heidelberg

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Abe, H., Tsumoto, S. (2011). Evaluating a Temporal Pattern Detection Method for Finding Research Keys in Bibliographical Data. In: Peters, J.F., et al. Transactions on Rough Sets XIV. Lecture Notes in Computer Science, vol 6600. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21563-6_1

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  • DOI: https://doi.org/10.1007/978-3-642-21563-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21562-9

  • Online ISBN: 978-3-642-21563-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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