Extracting product features and opinion words using pattern knowledge in customer reviews.
Due to the development of e-commerce and web technology, most of online Merchant sites are able to write comments about purchasing products for customer. Customer reviews expressed opinion about products or services which are collectively referred to as customer feedback data. Opinion extraction about products from customer reviews is becoming an interesting area of research and it is motivated to develop an automatic opinion mining application for users. Therefore, efficient method and techniques are needed to extract opinions from reviews. In this paper, we proposed a novel idea to find opinion words or phrases for each feature from customer reviews in an efficient way. Our focus in this paper is to get the patterns of opinion words/phrases about the feature of product from the review text through adjective, adverb, verb, and noun. The extracted features and opinions are useful for generating a meaningful summary that can provide significant informative resource to help the user as well as merchants to track the most suitable choice of product.
University of Computer Studies, Mandalay, Myanmar.
Su Su
SS
Htay
Machine and Research Department, University of Computer Studies, Mandalay, Myanmar.
Khin Thidar
KT
Lynn
D000465:Algorithms; D003132:Commerce; D003256:Community Participation / Q000706:statistics & numerical data*; D003258:Consumer Behavior / Q000706:statistics & numerical data*; D057225:Data Mining / Q000379:methods*; D006801:Humans; D020407:Internet; D011639:Public Opinion