Qualitative study in Natural Language Processing : text classification

Wahdan, A; Salloum, S; Shaalan, K

Abstract

Recently Natural Language Processing (NLP) has excessive attention due to increased data available online. Although there is huge development in Arabic NLP, but still it is behind English NLP. The aim of this study is to examine the most useful qualitative research design that can be used in the field of Arabic Natural Language Processing in general and in-text classification in specific. Two research designs have been examined in detail; survey and experimental research. Both benefits and drawbacks illustrated for each research design with examples for each method. Thus to have better understanding for some of the research methods. Then deciding which one is best fit to design a qualitative study in this field. Furthermore, this paper suggested framework can be used while researching in the field of NLP. The framework suggested to start with survey or Literature review then follow it with experiment.

Citation

Wahdan, A., Salloum, S., & Shaalan, K. (2022). Qualitative study in Natural Language Processing : text classification. Lecture notes in networks and systems (Online), 2, 83-92. https://doi.org/10.1007/978-3-030-85990-9_8

• Journal Article Type: Conference Paper
• Conference Name: International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021)
• Conference Location: Online
• End Date: Apr 6, 2021
• Online Publication Date: Dec 3, 2021
• Publication Date: Jan 1, 2022
• Deposit Date: Mar 4, 2022
• Journal: Proceedings of International Conference on Emerging Technologies and Intelligent Systems
• Print ISSN: 2367-3370
• Electronic ISSN: 2367-3389
• Volume: 2
• Pages: 83-92
• Series Title: Lecture Notes in Networks and Systems
• Series Number: 322
• Book Title: Proceedings of International Conference on Emerging Technologies and Intelligent Systems
• ISBN: 9783030859893-(softcover);-9783030859909-(ebook)
• DOI: https://doi.org/10.1007/978-3-030-85990-9_8
• Publisher URL: https://doi.org/10.1007/978-3-030-85990-9_8
• Related Public URLs: https://doi.org/10.1007/978-3-030-85990-9
• Additional Information: Event Type : Conference