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CVPR
2008
IEEE
14 years 8 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
KDD
2009
ACM
190views Data Mining» more  KDD 2009»
14 years 6 months ago
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
Gu Xu, Shuang-Hong Yang, Hang Li
CORR
2012
Springer
220views Education» more  CORR 2012»
12 years 2 months ago
Sparse Topical Coding
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
Jun Zhu, Eric P. Xing
ACL
2012
11 years 8 months ago
Pattern Learning for Relation Extraction with a Hierarchical Topic Model
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
Enrique Alfonseca, Katja Filippova, Jean-Yves Delo...
ICDM
2010
IEEE
197views Data Mining» more  ICDM 2010»
13 years 4 months ago
D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification
: D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi HP Labo...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...