• Mr.V.AJAY KUMAR
• S.SHAREEN
• M.KIRANMAI,

Now a day’s technology changes for publicity, way to traditional marketing also changes as person to-person communication to online reviews. As feedback these online reviews are important so customer and to companies or vendors. These reviews are helpful for making decisions regarding quality of products and services. Companies and vendors use opinions for making a decision for marketing strategies, performance to services or product, for improvement. However, the intentions to all customers of users are not true for writing reviews. This concept, changes the face of advertising to conventional, individual-to-individual correspondence to online audits. These online audits are important to client and to organizations or sellers. In this paper we proposed the method to recognizing the untruthful reviews that are given by the users which is having distinct semantic content based on sentiment analysis as the reviews of product. In this paper author represent to detect the spam untruthful reviews of product. For this classification we used J48 classifier. We generate ARFF from the distinct features to detecting the untruthful reviews. Using Support Count in Association Rules we further detect Brands in Fake Reviews.

Marketing Strategies, Semantic content, Sentiment analysis, ARFF, J48 classifier, etc.

"DETECTION OF FAKE REVIEW AND BRAND SPAM USING DATA MINING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.101-103, April-2019, Available :http://www.jetir.org/papers/JETIRBE06019.pdf

"DETECTION OF FAKE REVIEW AND BRAND SPAM USING DATA MINING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp101-103, April-2019, Available at : http://www.jetir.org/papers/JETIRBE06019.pdf