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A Hybrid Learning Approach for Text Classification Using Natural Language Processing

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Proceedings of the 5th International Conference on Big Data and Internet of Things (BDIoT 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 489))

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Abstract

Text classification and categorization is a hot topic that involves assigning tags or categories to a text based on its content. It is one of the important tasks of automatic natural language processing (NLP) in many applications such as topic tagging, sentiment analysis, intent detection, spam filtering, and email routing. Machine learning text classification can support businesses to automatically analyze and structure their textual documents promptly and inexpensively, to automate processes and improve data-driven decisions. In this article, we propose a new algorithm to classify textual documents using a hybrid approach that combines a set of given algorithms, using the best for each class. These documents can be classified into a set of possible class labels given a priori. Two machine learning algorithms are used to evaluate our proposed approach: Naive Bayesian (NB) and Logistic Regression (LR). The obtained results showed that the proposed hybrid algorithm is more efficient than NB and LR algorithms with an accuracy of 91.86%.

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Author information

Authors and Affiliations

  1. Hassan First University of Settat, Institute of Sports Sciences, Computer, Networks, Modeling, and Mobility Laboratory (IR2M), B.P. 539, 26000, Settat, Morocco

    Iman El Mir

  2. Hassan First University of Settat, Faculty of Sciences and Techniques, Computer, Networks, Modeling, and Mobility Laboratory (IR2M), B.P. 577, 26000, Settat, Morocco

    Said El Kafhali & Abdelkrim Haqiq

Authors
  1. Iman El Mir
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  2. Said El Kafhali
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  3. Abdelkrim Haqiq
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Corresponding author

Correspondence to Said El Kafhali .

Editor information

Editors and Affiliations

  1. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  2. UNILEHAVRE, UNIROUEN, Normandie Université, Le Havre, France

    Claude Duvallet

  3. Vrije Universiteit Brussel, Brussels, Belgium

    Abdellah Touhafi

  4. ENSA, Abdelmalek Essaâdi University, Tetuan, Morocco

    Mohammed Al Achhab

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El Mir, I., El Kafhali, S., Haqiq, A. (2022). A Hybrid Learning Approach for Text Classification Using Natural Language Processing. In: Lazaar, M., Duvallet, C., Touhafi, A., Al Achhab, M. (eds) Proceedings of the 5th International Conference on Big Data and Internet of Things. BDIoT 2021. Lecture Notes in Networks and Systems, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-07969-6_32

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