Main Reference PaperDual Sentiment Analysis: Considering Two Sides of One Review, IEEE Transactions on Knowledge and Data Engineering, Aug 2015.[python]
  • This paper proposes a technique to solve the polarity shift problem in sentiment classification. It proposes a model called as dual sentiment analysis (DSA) that contains two stages: 1) dual training (DT) and 2)dual prediction (DP). A dual training algorithm uses original and reversed training reviews in pairs for learning a sentiment classifier and a dual prediction algorithm classifies the test reviews by considering two sides of one review.

Description
  • This paper proposes a technique to solve the polarity shift problem in sentiment classification. It proposes a model called as dual sentiment analysis (DSA) that contains two stages: 1) dual training (DT) and 2)dual prediction (DP). A dual training algorithm uses original and reversed training reviews in pairs for learning a sentiment classifier and a dual prediction algorithm classifies the test reviews by considering two sides of one review.

  • The objective of the proposed work is to solve the problem sentiment classification.

  • To assist in supervised sentiment classification.

Aim & Objectives
  • The objective of the proposed work is to solve the problem sentiment classification.

  • To assist in supervised sentiment classification.

  • The existing of reversed reviews created based on supervised sentiment classification. The proposed system may contributes to create the reversed reviews based on unsupervised sentiment classification or imbalanced sentiment classification.

Contribution
  • The existing of reversed reviews created based on supervised sentiment classification. The proposed system may contributes to create the reversed reviews based on unsupervised sentiment classification or imbalanced sentiment classification.

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Project Recommended For
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Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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