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An Overview of Automatic Text Classification

Document Type : Research Paper

Authors

1 PhD student in Knowledge and Information Science, Knowledge Management, Tarbiat Modares University, Tehran, Iran

2 Assistant Professor, Department of Information Science and Epistemology, Tarbiat Modares University, Tehran, Iran

Abstract

Nowadays, various online resources are growing and disseminating rapidly. In order to organize these resources, attempts have been made to use automatic classification, which often uses statistical algorithms and machine learning. Recently, attention has been drawn to the use of library classifications. The main challenge here is that classification is an abstract, thought-provoking process, and machine techniques and artificial intelligence have not yet been able to completely replace the human mind. In this paper, we provide an overview of the importance of automatic classification, machine learning, and practical algorithms and techniques of clustering and classification like K-nearest neighbor, Bayesian models, artificial neural networks, deep learning, and hybrid classifications. Also, the steps of automatic classification of web pages and the techniques used in each step were mentioned. Achieving a clearer understanding of automatic classification will enable LIS experts to communicate with experts in the field of artificial intelligence and computers. This could pave the way for interdisciplinary research.

Keywords

References
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Knowledge Retrieval and Semantic Systems
Volume 9, Issue 32 - Serial Number 32
October 2022
Pages 191-219
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