HDLTex: Hierarchical Deep Learning for Text Classification
Kamran Kowsari,Donald E. Brown,Mojtaba Heidarysafa,Kiana Jafari Meimandi,Matthew S. Gerber,Laura E. Barnes +5 more
- pp 364-371
TLDR
Hierarchical Deep Learning for Text classification employs stacks of deep learning architectures to provide specialized understanding at each level of the document hierarchy.Abstract:
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an important application for supervised learning. Recently the performance of traditional supervised classifiers has degraded as the number of documents has increased. This is because along with growth in the number of documents has come an increase in the number of categories. This paper approaches this problem differently from current document classification methods that view the problem as multi-class classification. Instead we perform hierarchical classification using an approach we call Hierarchical Deep Learning for Text classification (HDLTex). HDLTex employs stacks of deep learning architectures to provide specialized understanding at each level of the document hierarchy.read more
Citations
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Journal ArticleDOI
Text Classification Algorithms: A Survey
Kamran Kowsari,Kiana Jafari Meimandi,Mojtaba Heidarysafa,Sanjana Mendu,Laura E. Barnes,Donald E. Brown +5 more
TL;DR: An overview of text classification algorithms is discussed, which covers different text feature extractions, dimensionality reduction methods, existing algorithms and techniques, and evaluations methods.
Journal ArticleDOI
Deep Learning--based Text Classification: A Comprehensive Review
TL;DR: This paper provided a comprehensive review of more than 150 deep learning-based models for text classification developed in recent years, and discussed their technical contributions, similarities, and strengths, and provided a quantitative analysis of the performance of different deep learning models on popular benchmarks.
Journal ArticleDOI
A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends
William G. Hatcher,Wei Yu +1 more
TL;DR: A thorough investigation of deep learning in its applications and mechanisms is sought, as a categorical collection of state of the art in deep learning research, to provide a broad reference for those seeking a primer on deep learning and its various implementations, platforms, algorithms, and uses in a variety of smart-world systems.
Posted Content
Deep Learning Based Text Classification: A Comprehensive Review
TL;DR: A comprehensive review of more than 150 deep learning--based models for text classification developed in recent years is provided, and their technical contributions, similarities, and strengths are discussed.
Journal ArticleDOI
Survey on supervised machine learning techniques for automatic text classification
TL;DR: Survey of text classification, process of different term weighing methods and comparison between different classification techniques are surveyed.
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