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Combining Apriori Approach with Support-Based Count Technique to Cluster the Web Documents

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 556))

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Abstract

The dynamic Web where thousands of pages are updated in every second is growing at lightning speed. Hence, getting required Web documents in a fraction of time is becoming a challenging task for the present search engine. Clustering, which is an important technique of data mining can shed light on this problem. Association technique of data mining plays a vital role in clustering the Web documents. This paper is an effort in that direction where the following techniques have been proposed:

  1. (1)

    a new feature selection technique named term-term correlation has been introduced which reduces the size of the corpus by eliminating noise and redundant features.

  2. (2)

    a novel technique named Support Based Count (SBC) has been proposed which combines with traditional Apriori approach for clustering the Web documents.

Empirical results on two benchmark datasets show that the proposed approach is more promising compared to the traditional clustering approaches.

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Notes

  1. 1.

    http://ai.stanford.edu/~rion/parsing/minipar_viz.html.

  2. 2.

    http://tartarus.org/martin/PorterStemmer/.

  3. 3.

    https://radimrehurek.com/gensim/tutorial.html.

  4. 4.

    http://qwone.com/~jason/20Newsgroups/.

  5. 5.

    http://www.dmoz.org.

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Author information

Authors and Affiliations

  1. BITS-Pilani, K.K. Birla Goa Campus, Sancoale, India

    Rajendra Kumar Roul & Sanjay Kumar Sahay

Authors
  1. Rajendra Kumar Roul
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  2. Sanjay Kumar Sahay
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Corresponding author

Correspondence to Rajendra Kumar Roul .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering & Information Technology, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of CSE, National Institute of Technology (NIT), Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Roul, R.K., Sahay, S.K. (2017). Combining Apriori Approach with Support-Based Count Technique to Cluster the Web Documents. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-10-3874-7_12

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  • DOI: https://doi.org/10.1007/978-981-10-3874-7_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3873-0

  • Online ISBN: 978-981-10-3874-7

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