Conceptual Semantic Model for Web Document Clustering Using Term Frequency

Authors

  • Dr. N. Krishnaraj Sasi Institute of Technology and Engineering
  • Dr P Kiran Kumar Sasi Institute of Technology and Engineering
  • Sri K Subhash Bhagavan Sasi Institute of Technology and Engineering

DOI:

https://doi.org/10.4108/eai.12-9-2018.155744

Keywords:

Clustering, Semantic Model, Text Mining, Term Frequency

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.

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Published

12-09-2018

How to Cite

1.
Krishnaraj DN, Kumar DPK, Subhash Bhagavan SK. Conceptual Semantic Model for Web Document Clustering Using Term Frequency. EAI Endorsed Trans Energy Web [Internet]. 2018 Sep. 12 [cited 2024 May 8];5(20):e14. Available from: https://publications.eai.eu/index.php/ew/article/view/966