TY  - JOUR
T1  - Finding Infrequent Features During Feature Extraction in Opinion
Mining Using Fuzzy Based Clustering
AU - Bharathi Mohan, G. AU - Ravi, T. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 22
SP  - 4546
EP  - 4550
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.4546.4550
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.4546.4550
KW  - Feature extraction
KW  -opinion mining
KW  -classification
KW  -sentiment analysis
KW  -web mining
AB  - With the growing trend of e-commerce sites, blogs and web forums, people are keenly articulating
their opinion on various products, topics. If we are buying a product for the first time, we would go through
reviews which are already presented by the users who have used it. Manual analysis can be difficult and
consumes more time, thus, a method is required to present the summary of the reviews. Reviews recorded by
the users are unstructured in nature. Opinion mining is a discipline of web content mining which in turn is a
category of web mining. The other categories of web mining are web structure and web usage mining. Opinion
mining can be exploited by both companies and individuals. It involves natural language processing, text
analysis and computational linguistics. The focus of the proposed system is mainly in extracting the aspects
or features of the product which is the first step of opinion mining. An extension to the Intrinsic and Extrinsic
Domain relevance method is made in order to support the rare features too. If the extraction step is improvised,
the consequent steps will give fine grained outcomes and thus the result will be enhanced greatly.
ER  -