Abstract
Text categorization is a crucial and well-proven method for organizing the collection of large scale documents. In this paper, we propose a hierarchical multi-class text categorization method with global margin maximization. We not only maximize the margins among leaf categories, but also maximize the margins among their ancestors. Experiments show that the performance of our algorithm is competitive with the recently proposed hierarchical multi-class classification algorithms. © 2009 ACL and AFNLP.
Cite
CITATION STYLE
Qiu, X., Gao, W., & Huang, X. (2009). Hierarchical multi-class text categorization with global margin maximization. In ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf. (pp. 165–168). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1667583.1667634
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