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Text Classification Algorithms: A Survey
by
Mendu, Sanjana
, Kowsari, Kamran
, Barnes, Laura
, Brown, Donald
, Heidarysafa, Mojtaba
, Jafari Meimandi, Kiana
in
Algorithms
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Discriminant analysis
/ document classification
/ Feature extraction
/ Information retrieval
/ Knowledge management
/ Machine learning
/ Natural language processing
/ Pipelines
/ Principal components analysis
/ text analysis
/ Text categorization
/ text classification
/ Text messaging
/ text mining
/ text representation
/ Texts
2019
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Text Classification Algorithms: A Survey
by
Mendu, Sanjana
, Kowsari, Kamran
, Barnes, Laura
, Brown, Donald
, Heidarysafa, Mojtaba
, Jafari Meimandi, Kiana
in
Algorithms
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Discriminant analysis
/ document classification
/ Feature extraction
/ Information retrieval
/ Knowledge management
/ Machine learning
/ Natural language processing
/ Pipelines
/ Principal components analysis
/ text analysis
/ Text categorization
/ text classification
/ Text messaging
/ text mining
/ text representation
/ Texts
2019
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Do you wish to request the book?
Text Classification Algorithms: A Survey
by
Mendu, Sanjana
, Kowsari, Kamran
, Barnes, Laura
, Brown, Donald
, Heidarysafa, Mojtaba
, Jafari Meimandi, Kiana
in
Algorithms
/ Classification
/ Data mining
/ Datasets
/ Deep learning
/ Discriminant analysis
/ document classification
/ Feature extraction
/ Information retrieval
/ Knowledge management
/ Machine learning
/ Natural language processing
/ Pipelines
/ Principal components analysis
/ text analysis
/ Text categorization
/ text classification
/ Text messaging
/ text mining
/ text representation
/ Texts
2019
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Journal Article
Text Classification Algorithms: A Survey
2019
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Overview
In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches have achieved surpassing results in natural language processing. The success of these learning algorithms relies on their capacity to understand complex models and non-linear relationships within data. However, finding suitable structures, architectures, and techniques for text classification is a challenge for researchers. In this paper, a brief overview of text classification algorithms is discussed. This overview covers different text feature extractions, dimensionality reduction methods, existing algorithms and techniques, and evaluations methods. Finally, the limitations of each technique and their application in real-world problems are discussed.
Publisher
MDPI AG
Subject
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