REVIEW ON COMPARATIVE EMOTION RECOGNITION SYSTEM FROM TEXT USING CLASSIFIER TECHNIQUES
The emotion recognition system is a generic model based on text and real-world knowledge. Recognition of Emotion from Text has noticeable and big problem in the Text-Processing Systems. In this paper, we proposed a review on emotion recognition from text with different types of classifier like Fuzzy Logic, Artificial Neural Network, and Support Vector Machine classifier. Most important methodology such as fuzzy logic towards Emotion Recognition from text using neural network has been discussed
... has been discussed in this paper. Emotions are indescribable things; however, there are lot of factors which can be used to recognized emotion from the text. In order to simplify the model by reducing the amount of data required to evaluate the propose model, we make use of fuzzy logic with neural network. Emotions and opinions have enormous impact on customers to make their choices regarding online-shopping, choosing-events, products and entities. These opinions also help the banks to propose plans and schemes for insurance zone. Application of the proposed work has high utility in detecting email spams by using the emotion recognition from the text data and artificial neural network enhanced the recognition efficiency of proposed module. By using the comparative study to recognize emotion from text we can achieve more accuracy as compare to previous work.