A correlation-based model for unsupervised feature selection
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Building semantic kernels for text classification using wikipedia
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting temporal contexts in text classification
Proceedings of the 17th ACM conference on Information and knowledge management
Classifying High-Dimensional Text and Web Data Using Very Short Patterns
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Exploiting Wikipedia as external knowledge for document clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Effective multi-label active learning for text classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Feature generation for text categorization using world knowledge
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Unsupervised relation extraction by mining Wikipedia texts using information from the web
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Ontology-based MEDLINE document classification
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Unsupervised feature selection for multi-cluster data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining positive and negative patterns for relevance feature discovery
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Unsupervised transfer classification: application to text categorization
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A Personalized Ontology Model for Web Information Gathering
IEEE Transactions on Knowledge and Data Engineering
High-precision phrase-based document classification on a modern scale
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
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The development of text classification techniques has been largely promoted in the past decade due to the increasing availability and widespread use of digital documents. Usually, the performance of text classification relies on the quality of categories and the accuracy of classifiers learned from samples. When training samples are unavailable or categories are unqualified, text classification performance would be degraded. In this paper, we propose an unsupervised multi-label text classification method to classify documents using a large set of categories stored in a world ontology. The approach has been promisingly evaluated by compared with typical text classification methods, using a real-world document collection and based on the ground truth encoded by human experts.