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ICDAR
2009
IEEE
16 years 1 months ago
Learning Rich Hidden Markov Models in Document Analysis: Table Location
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
Ana Costa e Silva
ICASSP
2008
IEEE
16 years 1 months ago
An iterative unsupervised learning method for information distillation
Information distillation techniques are used to analyze and interpret large volumes of speech and text archives in multiple languages and produce structured information of interes...
Kamand Kamangar, Dilek Hakkani-Tür, Gökh...
BIBM
2007
IEEE
135views Bioinformatics» more  BIBM 2007»
16 years 1 months ago
Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network
Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li
IJCNN
2007
IEEE
16 years 1 months ago
Integrating a Flexible Representation Machinery in a Model of Human Concept Learning
— High-order human cognition involves processing of abstract and categorically represented knowledge. Traditionally, it has been considered that there is a single innate internal...
Toshihiko Matsuka, Yasuaki Sakamoto
JCDL
2006
ACM
119views Education» more  JCDL 2006»
16 years 22 days ago
Learning from artifacts: metadata utilization analysis
Describes the MARC Content Designation Utilization Project, which is examining a very large set of metadata records as artifacts of the library cataloging enterprise. This is the ...
William E. Moen, Shawne D. Miksa, Amy Eklund, Serh...