News Aggregator Using SVM

  • Pooja Goel, Dr. G. Niranjana, Shikhar Srivastava

Abstract

The ultimate goal of this project will be to develop a news aggregation application. Regarding the sources of the news, it will be the HTML and the RSS (Rich Site Summary or Really Simple Syndication) Web Documents. The work of collecting news from various sources is done by using the Wrapper Program in Data Mining. This data is further parsed using a Parser that breaks it into required form. Further we use Machine Learning concept to store data from the training classifier to the android device memory. The existing aggregators either miss on one or other section of the news or are not able to put, news from one source, under one page. Here the focus will primarily lie on improving on the existing news aggregators in such a way that, this application will be able to fetch news from all those channels, who do not provide their complete news content on their RSS feeds. So basically one can fetch news from any of the desired news sources, all under, just one application. One amazing feature of the aggregator will be that the news will be live and fresh, for all news channels. A few features of the application will make it more user-friendly, for example giving priorities to your favourite news channel, etc.

Keywords: application, RSS, machine learning, SVM.

Published
2020-05-06
How to Cite
Pooja Goel, Dr. G. Niranjana, Shikhar Srivastava. (2020). News Aggregator Using SVM. International Journal of Advanced Science and Technology, 29(06), 2659 - 2669. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13727