Complex Events Processing on Live News Events Using Apache Kafka and Clustering Techniques

Aditya Kamleshbhai Lakkad, Rushit Dharmendrabhai Bhadaniya, Vraj Nareshkumar Shah and Lavanya K. (cb1dcf24-9f08-4fc8-B04b-47bbc153bc8e
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Aditya Kamleshbhai Lakkad: Vellore Institute of Technology, India
Rushit Dharmendrabhai Bhadaniya: Vellore Institute of Technology, India
Vraj Nareshkumar Shah: Vellore Institute of Technology, India
Lavanya K. (cb1dcf24-9f08-4fc8-B04b-47bbc153bc8e: Vellore Institute of Technology, India

International Journal of Intelligent Information Technologies (IJIIT), 2021, vol. 17, issue 1, 1-14

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.

Date: 2021
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