Supervised Sentiment Classification using DTDP algorithm |
Author(s): |
| S.Revathi , Priyadarshini Engineering College, Vaniyambadi.; B. Nagarajan, Priyadarshini Engineering College, Vaniyambadi. |
Keywords: |
| Natural Language Processing, Sentiment Analysis, Classification, Prediction |
Abstract |
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Sentiment analysis is the process widely used in all fields and it uses the statistical machine learning approach for text modeling. The primarily used approach is Bag-of-words (BOW). Though, this technique has some limitations in polarity shift problem. Thus, here we propose a new method called Dual sentiment analysis (DSA) which resolves the polarity shift problem. Proposed method involves two approaches such as dual training and dual prediction (DPDT). First, we propose a data expansion technique by creating a reversed review for training data. Second, dual training and dual prediction algorithm is developed for doing analysis on sentiment data. The dual training algorithm is used for learning a sentiment classifier and the dual prediction algorithm is developed for classifying the review by considering two sides of one review. |
Other Details |
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Paper ID: IJSRDV3I100450 Published in: Volume : 3, Issue : 10 Publication Date: 01/01/2016 Page(s): 645-648 |
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