Text and Document Classification Technologies

Text and Document Classification Technologies is a research topic within Artificial Intelligence. Science Explorer counts 23k research works in it since 1954. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of machine learning algorithms for multi-label text classification, with an emphasis on techniques such as feature selection, Naive Bayes classifier, K-nearest Neighbor (KNN), hierarchical classification, and support vector machines (SVM). The research covers various aspects of document categorization and information retrieval in the context of text mining and natural language processing.

• Multi-label Learning
• Text Classification
• Feature Selection
• Naive Bayes Classifier
• K-nearest Neighbor (KNN)
• Hierarchical Classification
• Machine Learning Algorithms
• Document Categorization
• Support Vector Machines (SVM)
• Information Retrieval