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KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 4 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
SEMWEB
2009
Springer
13 years 11 months ago
Learning to Map Ontologies with Neural Network
In this paper the authors applied the idea of training multiple tasks simultaneously on a partially shared feed forward network to domain of ontology mapping. A “cross trainingâ€...
Yefei Peng, Paul W. Munro, Ming Mao
ICAI
2009
13 years 2 months ago
Learning Mappings with Neural Network
The authors extended the idea of training multiple tasks simultaneously on a partially shared feed forward network. A shared input subvector was added to represented common inputs...
Yefei Peng, Paul W. Munro
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
14 years 5 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
ACL
2010
13 years 2 months ago
PCFGs, Topic Models, Adaptor Grammars and Learning Topical Collocations and the Structure of Proper Names
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
Mark Johnson