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.
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