An Efficient Approach to Book Review Mining Using Data Classification

Abstract

Abstract. With the growing usage of internet and popularity of opinion-rich resources like online reviews, people are actively using information technology to know and form their opinion. These reviews give vital information about a product and can impinge on its demand in cyber space. In this paper we have presented a hybrid technique combining TF-IDF method with opinion analysis using multinomial Naïve Bayes Classification algorithm to mine data of online reviews of books thereby improving the review results. TF-IDF method uses weighted technique to compute the weight of a word in a document and opinion analysis gives the polarity about a particular product. We amalgamate both techniques to improvise the efficiency of the results which may consequently be used by recommender systems for better recommendations.