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A Practitioner's Approach to Problem-Solving using AI

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News Event Detection Methods Based on Big Data Processing Techniques

Author(s): Karan Purohit*, Rishabh Saklani, Veena Bharti, Mahaveer Singh Naruka, Satya Prakash Yadav and Upendra Singh Aswal

Pp: 117-129 (13)

DOI: 10.2174/9789815305364124010009

* (Excluding Mailing and Handling)

Abstract

This research presents a novel approach for detecting news events using big data processing techniques. The proposed method involves four key steps: crawling news data from various news portal websites, filtering noise and removing duplicates, performing named entity recognition and text summarization, detecting media events through text clustering and feature extraction, and finally displaying the detected news topics through an intuitive interface. By leveraging static and dynamic web page crawler technologies, this method harnesses the power of big data to effectively identify and track news events. Experimental results demonstrate the effectiveness of the proposed approach in accurately detecting and presenting news topics.

Keywords: Big data processing, Feature extraction, Interface, Noise filtering, News event detection, Named entity recognition, Text summarization, Text clustering, Web page crawler.

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