An overview of Automatic Text Classification

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 use statistical algorithms and machine learning. Rrecently, 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 the automatic classification will enable LIS experts to communication with the experts in the field of artificial intelligence and computers. This could pave the way for interdisciplinary researches.