ABSTRACT

Text mining is the process of exploratory text analysis either by automatic or semi-automatic means that helps finding previously unknown information. Text mining is a highly interdisciplinary research area, bringing together research insights from the fields of data mining, natural language processing, machine learning, and information retrieval. The amount of textual data available is too huge to be managed manually. An automatic system is needed to analyze and interpret the text. Some of the systems are semi automatic requiring user input to begin processing others are fully automatic producing output from the input corpus without guidance. The review literatures on trend detection indicates that much progress has been made toward automating the process of detecting emerging trends but there is room for improvement. In this work, we propose a Trend Detection and Predictive Analytics (TDPA) using Living Analytics to detect emerging trends from live data to cater the needs of various users irrespective of their domain. The system needs to serve as general purpose software that will help the users to identify and visualize current happenings pertaining to any domain in an efficient and user friendly way. The paper also aims at forecasting the future of the trends obtained in helping the users to look forward and make quick decisions.