Abstract
In this era of the internet, a huge amount of news articles are added every minute of everyday. As a result of this evergrowing amount of news articles, news retrieval systems are required to process the news articles frequently and intensively. The news retrieval systems that are in use today barely cope up with these data-intensive computations. Cloudpress 2.0 presented here, is designed and implemented to be scalable, robust and fault tolerant. It is designed in such a way that all the processes involved in news retrieval, such as fetching, text processing, image processing, indexing, storing and summarising, exploit MapReduce paradigm and use the power of the cloud computing. It uses novel approaches for parallel processing, for storing the news articles in a distributed database and for visualising them as a 3D visual. It uses Lucene-based indexing for efficient and faster retrieval. It also includes a novel query expansion feature for searching the news articles. Cloudpress 2.0 also allows on-the-fly, extractive summarisation of news articles based on the input query.
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