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Preeti Arora
BhagwanParshuram Institute of Technology, New Delhi, India
Computer Science & IT Electrical & Electronics Engineering

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An Approach for Big Data to Evolve the Auspicious Information from Cross-Domains Preeti Arora; Deepali Virmani; P.S. Kulkarni
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1539.868 KB) | DOI: 10.11591/ijece.v7i2.pp967-974

Abstract

Sentiment analysis is the pre-eminent technology to extract the relevant information from the data domain. In this paper cross domain sentimental classification approach Cross_BOMEST is proposed. Proposed approach will extract †ve words using existing BOMEST technique, with the help of Ms Word Introp, Cross_BOMEST determines †ve words and replaces all its synonyms to escalate the polarity and blends two different domains and detects all the self-sufficient words. Proposed Algorithm is executed on Amazon datasets where two different domains are trained to analyze sentiments of the reviews of the other remaining domain. Proposed approach contributes propitious results in the cross domain analysis and accuracy of 92 % is obtained. Precision and Recall of BOMEST is improved by 16% and 7% respectively by the Cross_BOMEST.
Co-Authors Deepali Virmani P.S. Kulkarni