Features extraction based on Naive Bayes algorithm and TF-IDF for news classification

The rapid proliferation of online news demands robust automated classification systems to enhance information organization and personalized recommendation. Although traditional methods like TF-IDF with Naive Bayes provide foundational solutions, their limitations in capturing semantic nuances and ha...

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Veröffentlicht in:	PloS one Jg. 20; H. 7; S. e0327347
1. Verfasser:	Zhang, Li
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 30.07.2025 Public Library of Science (PLoS)
Schlagworte:	Accuracy Algorithms Bayes Theorem Biology and Life Sciences Classification Classification systems Computational linguistics Computer and Information Sciences Datasets Deep learning Documents Electronic news gathering Engineering and Technology Humans Identification and classification Inference Knowledge representation Language processing Latency Machine Learning Methods Natural language interfaces Natural Language Processing Neural networks News Physical Sciences Real time Research and Analysis Methods Semantics Social Sciences Statistical analysis Support vector machines Text categorization China
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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