Tuesday 21st of November 2017
 

Subjectivity Classification using Machine Learning Techniques for Mining Feature-Opinion Pairs from Web Opinion Sources


Ahmad Kamal

Due to flourish of the Web 2.0, web opinion sources are rapidly emerging containing precious information useful for both customers and manufactures. Recently, feature based opinion mining techniques are gaining momentum in which customer reviews are processed automatically for mining product features and user opinions expressed over them. However, customer reviews may contain both opinionated and factual sentences. Distillations of factual contents improve mining performance by preventing noisy and irrelevant extraction. In this paper, combination of both supervised machine learning and rule-based approaches are proposed for mining feasible feature-opinion pairs from subjective review sentences. In the first phase of the proposed approach, a supervised machine learning technique is applied for classifying subjective and objective sentences from customer reviews. In the next phase, a rule based method is implemented which applies linguistic and semantic analysis of texts to mine feasible feature-opinion pairs from subjective sentences retained after the first phase. The effectiveness of the proposed methods is established through experimentation over customer reviews on different electronic products.

Keywords: Subjectivity Classification, Machine Learning, Opinion Mining, Feature Identification.

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ABOUT THE AUTHOR

Ahmad Kamal
Ahmad Kamal is teaching Computer Science papers at the Department of Mathematics, Jamia Millia Islamia (A Central University), New Delhi, India. His qualification includes B.Sc. (H) Computer Applications, Post Graduate Diploma in Bioinformatics (PGDBIN), and Master of Computer Applications (MCA). Currently he is pursuing Ph.D. in Computer Science from the Department of Computer Science, Jamia Millia Islamia, New Delhi. He has more than 6 years of teaching experience at undergraduate and postgraduate levels. His research interests span over the area of opinion mining, natural language processing and machine learning.


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