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Determining Number of Clusters Using Firefly Algorithm with Cluster Merging for Text Clustering

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Advances in Visual Informatics (IVIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9429))

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Abstract

Text mining, in particular the clustering is mostly used by search engines to increase the recall and precision of a search query. The content of online websites (text, blogs, chats, news, etc.) are dynamically updated, nevertheless relevant information on the changes made are not present. Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection. In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced. The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. Experiments utilizing the proposed aFAmerge were conducted on two datasets; 20Newsgroups and Reuter’s news collection. Results indicate that the aFAmerge generates a more robust and compact clusters than the ones produced by Bisect K-means and practical General Stochastic Clustering Method (pGSCM).

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Acknowledgments

Authors would like to thank the Malaysian Ministry of Higher Education for providing the financial support under the Fundamental Research Grant Scheme (s/o: 12894). Gratitude also goes to Universiti Utara Malaysia for helping in managing the study.

Author information

Authors and Affiliations

  1. School of Computing, College of Arts and Sciences, Universiti Utara Malaysia, 06010, Sintok, Kedah, Malaysia

    Athraa Jasim Mohammed, Yuhanis Yusof & Husniza Husni

  2. University of Technology, Baghdad, Iraq

    Athraa Jasim Mohammed

Authors
  1. Athraa Jasim Mohammed
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  2. Yuhanis Yusof
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  3. Husniza Husni
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Corresponding author

Correspondence to Athraa Jasim Mohammed .

Editor information

Editors and Affiliations

  1. Fac Info Science and Techn, Universiti Kebangsaan Malaysia, Selangor, Malaysia

    Halimah Badioze Zaman

  2. University of Cambridge, Cambridge, United Kingdom

    Peter Robinson

  3. Center for Digital Video Process, Dublin 9, Ireland

    Alan F. Smeaton

  4. Computer Science and Information Enginee, National Central University, Jhongli City, Taiwan

    Timothy K. Shih

  5. Kingston University, Kingston upon Thames, United Kingdom

    Sergio Velastin

  6. Universiti Kebangsaan Malaysia, Institute of Visual Informatics, Bangi, Malaysia

    Azizah Jaafar

  7. Universiti Kebangsaan Malaysia, Institute of Visual Informatics, Bangi, Malaysia

    Nazlena Mohamad Ali

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Mohammed, A.J., Yusof, Y., Husni, H. (2015). Determining Number of Clusters Using Firefly Algorithm with Cluster Merging for Text Clustering. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2015. Lecture Notes in Computer Science(), vol 9429. Springer, Cham. https://doi.org/10.1007/978-3-319-25939-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-25939-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25938-3

  • Online ISBN: 978-3-319-25939-0

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