A Hybrid K-Means++ and Particle Swarm Optimization Approach for Enhanced Document Clustering

A Hybrid K-Means++ and Particle Swarm Optimization Approach for Enhanced Document Clustering

Document Clustering has attracted the interest of many researchers who have created several solutions to this problem by combining different techniques, models, and algorithms. While famous for its simplicity, the most commonly used algorithm, K-Means, suffers from issues such as finding the optimal...

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Bibliographic Details
Main Authors: Eisha Hassan, Fazila Malik, Qazi Waqas Khan, Nadeem Ahmad, Muhammad Sardaraz, Faten Khalid Karim, Hela Elmannai
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Optimization algorithm
feature extraction
PSO
text processing
decision making
Online Access:https://ieeexplore.ieee.org/document/10855427/
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