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

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 i...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of intelligent information technologies Vol. 17; no. 1; pp. 1 - 14
Main Authors Lakkad, Aditya Kamleshbhai, Bhadaniya, Rushit Dharmendrabhai, Shah, Vraj Nareshkumar, Lavanya K. (cb1dcf24-9f08-4fc8-b04b-47bbc153bc8e
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.01.2021
Subjects
Algorithms
Computational linguistics
Language processing
Machine learning
Methods
Natural language interfaces
Streaming media
Online AccessGet full text
ISSN1548-3657
1548-3665
1548-3665
DOI10.4018/IJIIT.2021010103

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1548-3657
1548-3665
1548-3665
DOI:10.4018/IJIIT.2021010103