Paper: Hierarchical Text Classification with Latent Concepts

ACL ID P11-2105
Title Hierarchical Text Classification with Latent Concepts
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Recently, hierarchical text classification has become an active research topic. The essential idea is that the descendant classes can share the information of the ancestor classes in a predefined taxonomy. In this paper, we claim that each class has several latent concepts and its subclasses share information with these d- ifferent concepts respectively. Then, we pro- pose a variant Passive-Aggressive (PA) algo- rithm for hierarchical text classification with latent concepts. Experimental results show that the performance of our algorithm is com- petitive with the recently proposed hierarchi- cal classification algorithms.