Matches in SemOpenAlex for { <https://semopenalex.org/work/W4367627723> ?p ?o ?g. }
- W4367627723 endingPage "236" @default.
- W4367627723 startingPage "236" @default.
- W4367627723 abstract "Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Widely used machine-learning-based research differs in terms of the datasets, training methods, performance evaluation, and comparison methods used. In this paper, we surveyed 224 papers published between 2003 and 2022 that employed machine learning for text classification. The Preferred Reporting Items for Systematic Reviews (PRISMA) statement is used as the guidelines for the systematic review process. The comprehensive differences in the literature are analyzed in terms of six aspects: datasets, machine learning models, best accuracy, performance evaluation metrics, training and testing splitting methods, and comparisons among machine learning models. Furthermore, we highlight the limitations and research gaps in the literature. Although the research works included in the survey perform well in terms of text classification, improvement is required in many areas. We believe that this survey paper will be useful for researchers in the field of text classification." @default.
- W4367627723 created "2023-05-02" @default.
- W4367627723 creator A5002183673 @default.
- W4367627723 creator A5042653526 @default.
- W4367627723 creator A5058425001 @default.
- W4367627723 date "2023-04-29" @default.
- W4367627723 modified "2023-09-29" @default.
- W4367627723 title "Twenty Years of Machine-Learning-Based Text Classification: A Systematic Review" @default.
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