Optimizing Document Classification: Unleashing the Power of Genetic Algorithms

Many individuals, including researchers, professors, and students, encounter difficulties when searching for scholarly documents, papers, and journals within a specific domain. Consequently, scholars have begun to focus on document classification problem, offering various methods to address this iss...

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Veröffentlicht in:	IEEE access Jg. 11; S. 83136 - 83149
Hauptverfasser:	Mustafa, Ghulam, Rauf, Abid, Al-Shamayleh, Ahmad Sami, Sulaiman, Muhammad, Alrawagfeh, Wagdi, Afzal, Muhammad Tanvir, Akhunzada, Adnan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	association for computing machinery (ACM) bag of word (BOW) Bit error rate Classification Classification algorithms Complexity Document classification (DC) Documents Feature extraction Genetic algorithms machine learning (ML) Metadata Optimization Semantics Support vector machines term frequency (TF) Word2Vector (W2V)
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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