Intelligent Information Extraction from Big Data Using Self Organizing Map

Knowledge extraction from social media has recently attracted great interest from the biomedical and health informatics community. Sentiment analysis has emerged as a popular and efficient technique for information retrieval and web data analysis. Such intelligent system improves healthcare outcomes and provides self-awareness using consumer opinion. The Proposed system uses natural language processing (NLP) which involves a two-step analysis framework that focuses on positive and negative sentimental analysis, as well as the side effects of treatment through users� forum posts. Regression process is used to merge the data from two-step analysis by using NLP approach. Finally self-Organizing Map (SOM) is enabled to classify the merged data. After classification SOM analyze the data by knowledge learning and token value is assigned for each medicine. Here token values play a vital role to list the appropriate medicines as per their priority. The proposed system may provide self-awareness to pupil by checking whether they are using the unbanned and effective medicine, thereby increasing healthcare outcomes by using user opinion from the medical web forum data.