In the same time, flames (such as rants, taunts, and squalid phrases) are offensive/abusive phrases which might attack or offend the users for a variety of reasons. An automatic discriminative software with a sensitivity parameter for flame or abusive language detection would be a useful tool.

A complete research and comparison of text mining concept using various stemming techniques(NLP). With the help of a case study (Twitter Sentiment Analysis) we have tried to analyse the output and taken the results.

A GUI based deep-learning chat-bot using tflearn, tensorflow, tkinter, lancaster stemmer, etc. It uses a json input file for training of the model and done !

AI Chatbot