Conceptual Semantic Model for Web Document Clustering Using Term Frequency

Krishnaraj, N. and Kumar, P. Kiran and Bhagavan, K Subhash (2018) Conceptual Semantic Model for Web Document Clustering Using Term Frequency. EAI Endorsed Transactions on Energy Web, 5 (20): e14. ISSN 2032-944X

[img]
Preview
Text
eai.12-9-2018.155744.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (1MB) | Preview

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.

Item Type: Article
Uncontrolled Keywords: Clustering, Semantic Model, Text Mining, Term Frequency
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 22 Sep 2020 13:53
Last Modified: 22 Sep 2020 13:53
URI: https://eprints.eudl.eu/id/eprint/555

Actions (login required)

View Item View Item