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Informative Article | Engineering Science | India | Volume 10 Issue 6, June 2021
A Comprehensive Examination of Techniques and Applications in Document Classification
Abstract: Document classification has important applications in information retrieval, data mining, and natural language processing and it involves categorizing documents into predefined classes. This survey paper offers a comprehensive overview of state-of-the-art techniques in document classification. Document classification encompasses of traditional machine learning algorithms like logistic regression and decision trees, alongside deep learning models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Furthermore, the paper highlights recent advancements in transfer learning, multi-label classification, and domain adaptation, underscoring their significance in addressing challenges such as data scarcity and domain shift. By presenting these diverse approaches, this survey aims to provide researchers and practitioners with a comprehensive understanding of various document classification techniques, paving the way for future advancements in the field.
Keywords: Document Classification, Machine Learning, Deep Learning, Applications, Natural Language Processing, Text Processing
Edition: Volume 10 Issue 6, June 2021,
Pages: 1809 - 1812