QQ客服 官方微博 反馈留言

	Hierarchical topic integration through semi-supervised hierarchical topic modeling
	Mao, Xian-Ling ; He, Jing ; Yan, Hongfei ; Li, Xiaoming
	2012
英文摘要	Lots of document collections are well organized in hierarchical structure, and such structure can help users browse and understand these collections. Meanwhile, there are a large number of plain document collections loosely organized, and it is difficult for users to understand them effectively. In this paper we study how to automatically integrate latent topics in a plain collection with the topics in a hierarchical structured collection. We propose to use semi-supervised topic modeling to solve the problem in a principled way. The experiments show that the proposed method can generate both meaningful latent topics and expand high quality hierarchical topic structures. ? 2012 ACM.; EI; 0
语种	英语
DOI标识	10.1145/2396761.2398483
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/294572]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Mao, Xian-Ling,He, Jing,Yan, Hongfei,et al. Hierarchical topic integration through semi-supervised hierarchical topic modeling. 2012-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。