论文信息 - Recognizing Emotion in Text using Neural Network and Fuzzy Logic

Recognizing Emotion in Text using Neural Network and Fuzzy Logic

Objectives: To find out sentiment of people about a particular thing or objects and to classify these sentiments. Methods: The common dialect handling techniques like fuzzy logic and neural system to be used extract emotions from text present in various blogs using MATLAB. Findings: The results show that with Neural Network and Fuzzy Logic performs very well in recognizing the emotional polarity of the sentences. From result simulations it has been concluded that the proposed method worked well having accuracy of 90% and able to classify the text according to their class (Happy, Sad and Anger). Improvements: The proposed method achieves better results in terms of Accuracy, Precision, Sensitivity and Specificity.

Gourav Bathla | Neeraj Kanger

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