#6422. Enhancing topic clustering for Arabic security news based on k-means and topic modelling

November 2026publication date
Proposal available till 30-05-2025
4 total number of authors per manuscript4010 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Control and Optimization;
Management Science and Operations Research;
Computer Networks and Communications;
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Abstract:
This study explores the feasibility of lightweight preprocessing techniques that transform a matrix of terms based on a survey of popular websites that publish security-related articles. Topic models perform soft clustering, allowing a document or term to refer to multiple topics at once with different probabilities. The work uses lexical data analysis with visualized data representations. The topic modeling approach used can effectively extract important topics from the entire text collected from various Internet resources. Based on the research results, the proposed method has a high rounding factor with a large number of topics.
Keywords:
clustering, topic model, summarization, topic search, machine learning

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