A hybrid Sentiment Classification method using Neural Network and Fuzzy Logic

Abstract

Neural Network(NN) and fuzzy systems are suitable for determining the input-output relationships. NN contend with numeric and quantitative information whereas fuzzy systems can handle symbolic and qualitative information. Coupling of Neural Network and Fuzzy Logic results in an intelligent crossbreed system widely referred to as Neuro-fuzzy system (NFS) that exploits the most effective qualities of these two approaches expeditiously. The coupled system combines the human alike logical reasoning of fuzzy systems with the training and connectedness structure of neural network. In this paper, we propose a method for performing Sentiment Classification using an NN and fuzzy set theory. In this method input reviews are fuzzified by using Gaussian membership function and fuzzification matrix is build. This matrix is transposed and passed to Multilayer Perceptron Backpropagation Network(MLPBPN).