News Event Detection Methods Based on Big Data Processing Techniques
- Authors: Karan Purohit1, Rishabh Saklani2, Veena Bharti3, Mahaveer Singh Naruka4, Satya Prakash Yadav5, Upendra Singh Aswal6
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View Affiliations Hide Affiliations1 Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, India 2 Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, India 3 Department of Computer Science and Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, India 4 Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management (GLBITM), Greater Noida, India 5 School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida, Uttar Pradesh, India 6 Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, India
- Source: A Practitioner's Approach to Problem-Solving using AI , pp 117-129
- Publication Date: October 2024
- Language: English
News Event Detection Methods Based on Big Data Processing Techniques, Page 1 of 1
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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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