The DOI matches its Crossref record; 185 of the 185 references it cites were found in a registry or an index.
A recent overview of the state-of-the-art elements of text classification
Open accessAbstract
The aim of this study is to provide an overview the state-of-the-art elements of text classification. For this purpose, we first select and investigate the primary and recent studies and objectives in this field. Next, we examine the state-of-the-art elements of text classification. In the following steps, we qualitatively and quantitatively analyse the related works. Herein, we describe six baseline elements of text classification including data collection, data analysis for labelling, feature construction and weighing, feature selection and projection, training of a classification model, and solution evaluation. This study will help readers acquire the necessary information about these elements and their associated techniques. Thus, we believe that this study will assist other researchers and professionals to propose new studies in the field of text classification.
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Cites
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Clinical text classification research trends: Systematic literature review and open issues
Mujtaba, G., Shuib, L., Idris, N., Hoo, W. L., Raj, R. G., Khowaja, K., Shaikh, K., & Nweke, H. F. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.09.034 · Cited by 123
Metadata
- Authors
- Mirończuk, M. M., & Protasiewicz, J.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 106
- Pages
- 36-54
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2802787326
- Cited by
- 317
- References
- 185
- FWCI
- 19.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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