SMART INFORMATION RETRIEVAL - QUESTION ANSWERING AND SUMMARY GENERATION USING BERT
Author(s):
Bhavesh Satpute, Bhushan Sawant, Sushant Yelurkar, Omkar Dighe, Rashmi Jolhe
Keywords:
Fast information retrieval, Relevant Information, Real-time data, Chrome Extension, Current webpage, PDF, Search on a user query.
Abstract
Over the years, we are studying web pages, technical papers, research papers, etc. The traditional method of retrieving a piece of information from a large collection of data or information was manual searching and it was taking huge time. But in today’s fast world, we used this information retrieval concept to find data in seconds. So, it becomes a fast and less time-consuming method for retrieving information. Even though its retrieving speed has increased but the quality of information is less. So, to overcome this we introduced Smart Information Retrieval where the user will get the relevant information on the basis of the user query, and also the user will get the summary on the basis of the Abstract, we classify this abstract in labels like Background, Methodology, Objective, Result, Conclusion. The accuracy of the predicted answer based on the user query is more the 70% and the relevancy of the generating summary or classifying the Abstract is 87%. This ability to predict answers and generate a summary or classify the Abstract from the given input makes this information retrieval system different from others.
Article Details
Unique Paper ID: 159526

Publication Volume & Issue: Volume 9, Issue 12

Page(s): 154 - 160
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