INTENT EXTRACTION FROM TEXT BY USING GLOBAL FEATURE MATRIX TO IMPROVE MAN MACHINE INTERACTION

Interaction between man and machine is the future of technology. Different mechanisms and mediums are used for this interaction such as voice, signals, pictures, videos, text etc. Text is one of the most popular medium of interaction and has gained popularity over past decades. It is used for making predictions of stock market, analysis of people’s opinion, identification of group of people with similar interests etc. In this research, the focus is to identify and analyze the intent of the written text and used it to prepare an appropriate machine response to text. There are several system available that uses semi-automatic mechanisms for interaction with humans such as the online customer care services for banks and the telecommunication industry. Different models and algorithms are used for this semi-automatic interaction. This study works on the design of a fully automated system for extracting the intents from the text, prepare an appropriate response and use the intent to do the prediction of the text. The results of the research are detailed in the methodology and experiment sections of the paper.