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BMCBI
2010
179views more  BMCBI 2010»
15 years 6 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
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...
COOPIS
2003
IEEE
15 years 12 months ago
Mining for Lexons: Applying Unsupervised Learning Methods to Create Ontology Bases
Ontologies in current computer science parlance are computer based resources that represent agreed domain semantics. This paper first introduces ontologies in general and subseque...
Marie-Laure Reinberger, Peter Spyns, Walter Daelem...
AIME
2003
Springer
15 years 12 months ago
The NewGuide Project: Guidelines, Information Sharing and Learning from Exceptions
Among the well agreed-on benefits of a guideline computerisation, with respect to the traditional text format, there are the disambiguation, the possibility of looking at the guide...
Paolo Ciccarese, Ezio Caffi, Lorenzo Boiocchi, Ass...