Smart Patient Records using NLP and Blockchain

Text summarizing is the process of condensing text such that extraneous information is deleted and only the most important information is extracted and presented in the most understandable manner. Due to the exponential growth of social media data, it is now essential to assess this text in order to extract statistics, particulars and utilize it to the best benefit of several requisitions, applications and implementations. In recent years, the natural language processing and text mining communities have been more interested in the problem of automated summarizing, chiefly on the topic of opinion summarization. In society, views are essential for making decisions. A person or corporation depends on the advice and opinions of others while making choices. In this study, we provide a graph-based technique for creating summaries of repeated points of view and integrating the claims using sentiment analysis. The resultant summaries are carefully crafted to convey the text’s core and are based on abstraction.