Publication

Abstract : Emotions finding from stories is a wide range area of research with lot of different applications. Through this research work, we are trying to predict the effect of emotion from stories with the help of ensemble classifiers. Stories are an essential part of childhood. It is an effective way for children to understand the environment and things happening around the world. The story telling will help them to develop good manners and intellectual power. It will definitely impact the behavior of children like through the situations described in the story. The basic emotions in kids square measure joy, fear, anger, disgust, surprise, disappointment and neutral. The degree of those emotions depends upon the essential character of kid. Classification is an important data mining technique which is used here to classify the sentences in the stories based on the emotion reflected in the child. Here, we are examining the efficiency of classification algorithms for creating the prediction models from children stories. For that, we are using both single and ensemble classifiers, which help us to make good comparison for story-based emotion experiment because it shows 80% accuracy and takes only less time to build model using both classifiers.