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Paper Details
Paper Title
Mining Online Reviews in Websites for Predicting Sales Performance
Authors
  Divagar S,  Joesph Raymond V
Abstract
Nowadays people posting reviews are increasing and it gives us the knowledge to buy the products. People can express their sentiments through reviews posted in websites. By these reviews we can predict the movie sales performance. The question is how the sentiment factor can be analyzed in the reviews? Reviews are analyzed by Sentiment PLSA which helps us to find the unknown factors in the reviews and helps us to classify the reviews. Then we have to predict the sales performance, for the prediction regression is suitable way to do and we suggest an autoregressive sentiment (ARSA) Aware Model. To improve the prediction accuracy to enhance the best quality factor we also consider an autoregressive sentiment and quality aware model (ASQA)to build the quality for mining reviews sales performance in movie domain.
Keywords- OnlineReview mining, hidden sentiment analysis, prediction, S-PLSA, ARSA
Publication Details
Unique Identification Number - IJEDR1401211Page Number(s) - 1184-1186Pubished in - Volume 2 | Issue 1 | March 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Divagar S,  Joesph Raymond V,   "Mining Online Reviews in Websites for Predicting Sales Performance", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 1, pp.1184-1186, March 2014, Available at :http://www.ijedr.org/papers/IJEDR1401211.pdf
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