The era of information technology has grown tremendously over the decade. In the existing opinion mining technology, the response time and the accuracy are not up to the expectation. The sentiment analysis is not accurate in the traditional systems. The method failed to divide the opinion holder, tendency and the opinion object from the opinion given by the holder/user and it results to the failure in obtaining the overall report of the positive and negative feedbacks of the object. The proposed fine grained opinion mining can perform better in analyzing the holder, tendency, and expression from the statement. This accuracy of the proposed system is consistent in the case of large datasets such as reading the reviews of the customers and filters the positive and negative opinion in an accurate manner. The proposed system uses the external sentiment directory for comparing the opinion given by the user and predefined emotional data stored in the directory.
S. Gnanapriya
Kovai Kalaimagal College of Arts and Science, India
Opinion Mining, Sentiment Analysis, Emotional Mining, Conditional Random Field, Machine Learning
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| Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 13 , Issue: 3 , Pages: 2931 - 2939 )
Date of Publication :
April 2023
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