ew 18(20): e14

Research Article

Conceptual Semantic Model for Web Document Clustering Using Term Frequency

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  • @ARTICLE{10.4108/eai.12-9-2018.155744,
        author={Dr. N. Krishnaraj and Dr P Kiran Kumar and Sri K Subhash Bhagavan},
        title={Conceptual Semantic Model for Web Document Clustering Using Term Frequency},
        journal={EAI Endorsed Transactions on Energy Web and Information Technologies},
        volume={5},
        number={20},
        publisher={EAI},
        journal_a={EW},
        year={2018},
        month={9},
        keywords={Clustering, Semantic Model, Text Mining, Term Frequency},
        doi={10.4108/eai.12-9-2018.155744}
    }
    
  • Dr. N. Krishnaraj
    Dr P Kiran Kumar
    Sri K Subhash Bhagavan
    Year: 2018
    Conceptual Semantic Model for Web Document Clustering Using Term Frequency
    EW
    EAI
    DOI: 10.4108/eai.12-9-2018.155744
Dr. N. Krishnaraj1,*, Dr P Kiran Kumar1, Sri K Subhash Bhagavan2
  • 1: Professor, Sasi Institute of Technology and Engineering
  • 2: Assistant Professor, Sasi Institute of Technology and Engineering
*Contact email: krishnaraj@sasi.ac.in

Abstract

Term analysis is the key objective of most of the methods under text mining, here term analysis either refers to a word or a phrase. Determination of the documents subject is another important task to be performed by the semantic based method; this is done by identifying those expressions that resemble the semantics of a sentence. This model in general is called as the mining model and it is exclusively used to identify either the words or the expressions in a document on each and every specific sentence, this identification can also be done at the core level. As far as a group of documents is concerned the proposed method is capable of identifying the similar concepts among them; this identification is done by analysing the sentence semantics among the documents. The prime focus is to improve the quality of the web document clustering method, this is done by analysing the semantics of the sentences efficiently and thereafter organising the same effectively.