Paper Title :Topic Modelling with News Summary

Author :Sahil Sachin Donde, Renuka Devi S

Article Citation :Sahil Sachin Donde ,Renuka Devi S , (2023 ) " Topic Modelling with News Summary " , International Journal of Soft Computing And Artificial Intelligence (IJSCAI) , pp. 47-56, Volume-11,Issue-1

Abstract : A huge amount of data is been collected on daily-basis. Many times, it becomes difficult to find the exact content what we are looking for. This arises the need for some advanced tools and techniques which can search and organize the data, thus help to understand the information.It is very important to read news or be aware of what is happening in and around. But the problem is that in news articles we have a lot of paragraphs which feels very bored to the students or to many people. Getting a gist or a summarized view of the news would be very helpful for them. Also, many a times people want to see news of a specific domain like sports, films, politics, education, etc. but in news articles we see all news together. It would have been better to give a topic and assign the summarized news under each topic. Similarly for any ECommerce shopping portals, where people want to see the reviews of products where instead of reading all reviews serially, one can select a topic and only the reviews related to that topic would be displayed. The purpose of this paper is to propose a strategy of solving the issue of reading huge text and to get the exact topic content. It uses Natural Language Processing (NLP) and Extractive Text Summarization algorithms to generate summarized text. Using Latent Dirichlet Allocation, a suitable topic is assigned for the generated summarized text. Keywords - Extractive text summarization, Abstractive Text Summarization, Latent Dirichlet Allocation, Natural Language Processing.

Type : Research paper

Published : Volume-11,Issue-1

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