A Combined Model of NLP with Business Process Modelling for Sentiment Analysis

Natural language processing is one of the main sub-field of artificial intelligence, where all end users of internet in real time use their native language to extract the required information. This work concentrates on the sentiment analysis on social media, which comprises of text, numbers, hashtags, symbolic representations and much more. It becomes tedious in handling these unstructured data. Hence, the solution is to makes use of basic NLP tools, then implement Markov decision process in order to process the translation of the native language input to a SQL query. An implementation idea for business process models is also incorporated to have different analysis states of the input data. The accuracy achieved through Deep learning models in this proposed work are greater compared to the other machine learning and normal corpus methodologies.