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Online Review Mining for Forecasting Sales


Affiliations
1 Department of BCA, PSGR Krishnammal College for Women, Coimbatore
2 Department of BCA, PSGR Krishnammal College for Women, Coimbatore, India
     

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The growing popularity of online product review forums invites people to express opinions and sentiments toward the products .It gives the knowledge about the product as well as sentiment of people towards the product. These online reviews are very important for forecasting the sales performance of product. In this paper, we discuss the online review mining techniques in movie domain. Sentiment PLSA which is responsible for finding hidden sentiment factors in the reviews and ARSA model used to predict sales performance. An Autoregressive Sentiment and Quality Aware model (ARSQA) also in consideration for to build the quality for predicting sales performance. We propose clustering and classification based algorithm for sentiment analysis.


Keywords

Online Review Mining, Text Mining, Reviews, S-PLSA, ARSA, Clustering, Classification.
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  • Online Review Mining for Forecasting Sales

Abstract Views: 207  |  PDF Views: 3

Authors

S. Keerthana
Department of BCA, PSGR Krishnammal College for Women, Coimbatore
J. Jaishree
Department of BCA, PSGR Krishnammal College for Women, Coimbatore, India

Abstract


The growing popularity of online product review forums invites people to express opinions and sentiments toward the products .It gives the knowledge about the product as well as sentiment of people towards the product. These online reviews are very important for forecasting the sales performance of product. In this paper, we discuss the online review mining techniques in movie domain. Sentiment PLSA which is responsible for finding hidden sentiment factors in the reviews and ARSA model used to predict sales performance. An Autoregressive Sentiment and Quality Aware model (ARSQA) also in consideration for to build the quality for predicting sales performance. We propose clustering and classification based algorithm for sentiment analysis.


Keywords


Online Review Mining, Text Mining, Reviews, S-PLSA, ARSA, Clustering, Classification.