Adaptive Binary Bat and Markov Clustering Algorithms for Optimal Text Feature Selection in News Events Detection Model

Wrapper Feature Selection (FS) methods based on the Binary Bat Algorithm (BBA) have recently been employed in a variety of detection applications to determine the most relevant feature subset. Despite the outstanding achievement of BBA in these domains, BBA has never been applied in Event Detection...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE access Ročník 10; s. 85655 - 85676
Hlavní autoři:	Al-Dyani, Wafa Zubair, Ahmad, Farzana Kabir, Kamaruddin, Siti Sakira
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Adaptive systems adaptive techniques Algorithms Binary bat algorithm (BBA) Clustering Convergence Datasets Documents Event detection event detection (ED) Feature extraction Feature selection feature selection (FS) heterogeneous news Loudness Markov clustering (MCL) Markov processes News Optimization Performance enhancement Production methods Social networking (online) text clustering wrapper methods
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!