International Journal of Mathematical Sciences and Computing (IJMSC)
IJMSC Vol. 2, No. 2, 8 Apr. 2016
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Research Domain Selection using Naive Bayes Classification
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Author(s)
Index Terms
Research Domain Selection, Information Retrieval, Text mining, Classification
Abstract
Research Domain Selection plays an important role for researchers to identify a particular document based on their discipline or research areas. This paper presents a framework which consists of two phases. In the first phase, a word list is constructed for each area of the research paper. In the second phase, the word list is continuously updated based on the new domains of research documents. Primary area and Sub area of the documents are identified by applying pre-processing and text classification techniques. Naive Bayes classifier is used to find the probability of various areas. An area having the highest probability is considered as primary area of the document. In this paper text classification procedures is condensed as that are utilized to arrange the content archives into predefined classes. Based on the performance analysis, it has been observed that the obtained results are efficient when compared to manual judgement.
Cite This Paper
Selvani Deepthi Kavila, Radhika Y,"Research Domain Selection using Naive Bayes Classification", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.2, No.2, pp.14-23, 2016.DOI: 10.5815/ijmsc.2016.02.02
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