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Complex Events Processing on Live News Events Using Apache Kafka and Clustering Techniques
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Author(s): Aditya Kamleshbhai Lakkad (Vellore Institute of Technology, India), Rushit Dharmendrabhai Bhadaniya (Vellore Institute of Technology, India), Vraj Nareshkumar Shah (Vellore Institute of Technology, India) and Lavanya K. (Vellore Institute of Technology, India)
Copyright: 2021
Volume: 17
Issue: 1
Pages: 14
Source title:
International Journal of Intelligent Information Technologies (IJIIT)
Editor(s)-in-Chief: Vijayan Sugumaran (Oakland University, USA)
DOI: 10.4018/IJIIT.2021010103
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Abstract
The explosive growth of news and news content generated worldwide, coupled with the expansion through online media and rapid access to data, has made trouble and screening of news tedious. An expanding need for a model that can reprocess, break down, and order main content to extract interpretable information, explicitly recognizing subjects and content-driven groupings of articles. This paper proposed automated analyzing heterogeneous news through complex event processing (CEP) and machine learning (ML) algorithms. Initially, news content streamed using Apache Kafka, stored in Apache Druid, and further processed by a blend of natural language processing (NLP) and unsupervised machine learning (ML) techniques.
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