Adaptive Markov Clustering Algorithm for Optimal Event Detection From Heterogeneous News Documents

Several Event Detection (ED) applications utilize various wrapper Feature Selection (FS) techniques based on wrapping the Markov Clustering Algorithm (MCL) with the Binary Bat Algorithm (BBA) or Adaptive Bat Algorithm (ABBA). These approaches have shown promising results in identifying relevant feat...

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Vydané v:	IEEE access Ročník 12; s. 72079 - 72097
Hlavný autor:	Al-Dyani, Wafa Zubair
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive algorithms Adaptive BBA Adaptive control adaptive techniques Algorithms Clustering Clustering algorithms Clusters Convergence Data models Datasets Effectiveness Event detection event detection (ED) methods Feature extraction Heterogeneous networks heterogeneous news Markov clustering (MCL) Markov processes News Planning Tuning wrapper methods
ISSN:	2169-3536, 2169-3536
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