A Novel Query Based Summerizer Model Of Product Reviews Using Modified LDA

In this digital era, there must be a system which can summarize huge lot of data and categorize the documents under specific topic without its semantic meaning being detached. Some important information can be extracted out of these documents as and when it is needed. The system can ease out many cumbersome processes which in other times might require a lot of manual work. Additionally, it becomes easy to navigate through a summarized version of a document rather than investigating a huge lot. The efficiency gets increased and manual work gets decreased. The system is basically an integrated version of both topic modelling and question answering with suitable machine learning algorithms. So, in short, the system works out to ease out some traditional work and can also be a solution to some technical problems related to storage and processing since a summarized version of the document given as input is only stored and further processed to give specific answers to the queries raised by the users.