Polarity Sentiment-Based Intelligent Chat Bot For Judicious Customer Service Escalation

Most of modern day Information Processing applications require Natural Language Processing. Most of the applications need extracting, processing of text to be done in their surface forms. Applications like document classification, text-extraction and machine translation comes under Natural Language Processing. Knowledge based approach of Natural Language Processing deals with representing and acquiring of knowledge to solve problems like ambiguity resolution. Ambiguities in Customer service conversation requires high level processing in order to generate the appropriate automated replies. Sentiment analysis is the interpretation of emotions and attitude of the user. Emotions can depend on mood of the user. In this work negative/positive probability is used to show the sentiment of a user which in turn can help the chat bot to generate a suitable reply to the user and escalate the conversation to a real representative when it sense that user is frustrated beyond a cutoff.