articleInformationApr 23, 2019GOLD OA

Text Classification Algorithms: A Survey

KKKamran KowsariKJKiana Jafari MeimandiMHMojtaba HeidarysafaSMSanjana MenduLBLaura Barnes

University of Virginia Health System · University of Virginia

Indexed inarxivcrossrefdoaj

Abstract

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…

Citation impact

1,256
total citations
FWCI
79.65
Percentile
100%
References
210
Citations per year

Authors

6
  • KK
    Kamran KowsariCorresponding

    University of Virginia Health System, University of Virginia

  • KJ
    Kiana Jafari Meimandi

    University of Virginia

  • MH
    Mojtaba Heidarysafa

    University of Virginia

  • SM
    Sanjana Mendu

    University of Virginia

  • LB
    Laura Barnes

    University of Virginia Health System, University of Virginia

Topics & keywords

Keywords
  • Dimensionality reduction
  • Feature (linguistics)
  • Natural language
  • Curse of dimensionality
  • Statistical classification
  • Natural language understanding
  • Support vector machine
No related works found for this paper.

Funding