@inproceedings{45028da47412415a8c0a86dccda394e8,
title = "Learning topic hierarchies for wikipedia categories",
abstract = "Existing studies have utilized Wikipedia for various knowledge acquisition tasks. However, no attempts have been made to explore multi-level topic knowledge con-tained in Wikipedia articles' Contents ta-bles. The articles with similar subjects are grouped together into Wikipedia cat-egories. In this work, we propose novel methods to automatically construct com-prehensive topic hierarchies for given cat-egories based on the structured Contents tables as well as corresponding unstruc-tured text descriptions. Such a hierarchy is important for information browsing, doc-ument organization and topic prediction. Experimental results show our proposed approach, incorporating both the structural and textual information, achieves high quality category topic hierarchies.",
author = "Linmei Hu and Xuzhong Wang and Mengdi Zhang and Juanzi Li and Xiaoli Li and Chao Shao and Jie Tang and Yongbin Liu",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics.; 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 ; Conference date: 26-07-2015 Through 31-07-2015",
year = "2015",
doi = "10.3115/v1/p15-2057",
language = "English",
series = "ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "346--357",
booktitle = "ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference",
address = "United States",
}
