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Survey on supervised machine learning techniques for automatic text classification

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Abstract

Supervised machine learning studies are gaining more significant recently because of the availability of the increasing number of the electronic documents from different resources. Text classification can be defined that the task was automatically categorized a group documents into one or more predefined classes according to their subjects. Thereby, the major objective of text classification is to enable users for extracting information from textual resource and deals with process such as retrieval, classification, and machine learning techniques together in order to classify different pattern. In text classification technique, term weighting methods design suitable weights to the specific terms to enhance the text classification performance. This paper surveys of text classification, process of different term weighing methods and comparison between different classification techniques.

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  1. Department of Computer Science, College of Medicine, University of Baghdad, Baghdad, Iraq

    Ammar Ismael Kadhim

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Kadhim, A.I. Survey on supervised machine learning techniques for automatic text classification. Artif Intell Rev 52, 273–292 (2019). https://doi.org/10.1007/s10462-018-09677-1

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