Online multi-label dependency topic models for text classification

Multi-label text classification is an increasingly important field as large amounts of text data are available and extracting relevant information is important in many application contexts. Probabilistic generative models are the basis of a number of popular text mining methods such as Naive Bayes o...

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Veröffentlicht in:	Machine learning Jg. 107; H. 5; S. 859 - 886
Hauptverfasser:	Burkhardt, Sophie, Kramer, Stefan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.05.2018 Springer Nature B.V
Schlagworte:	Artificial Intelligence Bayesian analysis Classification Computer Science Control Data mining Dirichlet problem Labels Machine learning Mechatronics Natural Language Processing (NLP) Robotics Simulation and Modeling Text editing Texts Training LDA Multi-label classification Online learning Topic model
ISSN:	0885-6125, 1573-0565
Online-Zugang:	Volltext
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