A new approach to represent textual documents using CVSM

  • Authors

    • Brahmananda Reddy
    • Sagar Y
    • Subhash P
    2018-11-16
    https://doi.org/10.14419/ijet.v7i4.15372
  • Machine learning, cognitive computing, data mining, artificial intelligence, pattern recognition.
  • Due to advancements in technology, a vast amount of data is produced which is generally in the form of unstructured data. This is where text mining finds its value to discover and retrieve useful information. Text mining is a process of seeking or extracting high quality in-formation. Generally, in text mining, Vector Space Model (VSM) is used which transforms unstructured data to structured data by the use of traditional keyword based approach. One of the problems with this approach is that if a user puts a query, the set of documents are retrieved which match the keywords in the query. To overcome this, a Conceptual Vector Space Model (CVSM) is described in this pa-per which helps to categorize different documents with the same content which may use different vocabulary. The Conceptual Vector Space Model is implemented with the help of WordNet, Natural Language ToolKit (NLTK).Clustering algorithms are applied on it to form clusters based on concepts.

  • References

    1. [1] Dr. G. Rasitha Banu, VK Chitra, A Survey of Text Mining Con-cepts, semanticsscholar.org, April 2015.
      [2] Niladri Biswas, Text Mining and its Business Applications, Sep-tember 2014.
      [3] A. Brahmananda Reddy, A. Govardhan “Integrated Feature Selec-tion Methods for Text Document Clusteringâ€, International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 10 No.81 (2015), PP: 153-158, Research India Publications.
      [4] https://wordnet.princeton.edu/.
      [5] https://www.nltk.org/.
      [6] Dr.S.Kannan, VairaprakashGurusamy, Preprocessing Techniques for Text Mining, Conference Paper, March 201.
      [7] E. E. Ogheneovo, R. B. Japheth, Application of Vector Space Mod-el to Query Ranking and Information Retrieval, International Jour-nal of Advanced Research in Computer Science and Software En-gineering, Vol. 6, Issue 5, May 2016.
      [8] Gerald J. Kowalski, Mark T. Maybury, Information Storage and Retrieval Systems, Theory and Implementation, 2006.
      [9] Brahmananda Reddy; A. Govardhan , A novel approach for similar-ity and indexing-based ontology for semantic web educational sys-tem, International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 4 No.2, 2016. https://doi.org/10.1504/IJIEI.2016.076698.
      [10] Dr. S. Vijayarani, Ms. J. Ilamathi, Ms. Nithya3, Preprocessing Techniques for Text Mining - An Overview, International Journal of Computer Science & Communication Networks, Vol 5(1), 7-16.
      [11] Vaibhav Kant Singh, Vinay Kumar Singh, Vector Space Model: An Information Retrieval System, International Journal of Advanced Engineering Research and Studies, 2015.
      [12] http://www.nltk.org/howto/wordnet.html.

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  • How to Cite

    Reddy, B., Y, S., & P, S. (2018). A new approach to represent textual documents using CVSM. International Journal of Engineering & Technology, 7(4), 4678-4682. https://doi.org/10.14419/ijet.v7i4.15372