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» Discovering and Comparing Topic Hierarchies
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EMNLP
2007
14 years 11 months ago
A Topic Model for Word Sense Disambiguation
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
Jordan L. Boyd-Graber, David M. Blei, Xiaojin Zhu
CVPR
2010
IEEE
15 years 5 months ago
Building and Using a Semantivisual Image Hierarchy
A semantically meaningful image hierarchy can ease the human effort in organizing thousands and millions of pictures (e.g., personal albums), and help to improve performance of en...
Li-Jia Li, Chong Wang, Yongwhan Lim, David Blei, L...
SIGIR
2008
ACM
14 years 9 months ago
A comparative evaluation of different link types on enhancing document clustering
With a growing number of works utilizing link information in enhancing document clustering, it becomes necessary to make a comparative evaluation of the impacts of different link ...
Xiaodan Zhang, Xiaohua Hu, Xiaohua Zhou
WWW
2011
ACM
14 years 4 months ago
Geographical topic discovery and comparison
This paper studies the problem of discovering and comparing geographical topics from GPS-associated documents. GPSassociated documents become popular with the pervasiveness of loc...
Zhijun Yin, Liangliang Cao, Jiawei Han, Chengxiang...
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CVPR
2008
IEEE
15 years 11 months ago
Unsupervised discovery of visual object class hierarchies
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...