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» Information extraction, data mining and joint inference
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GRC
2010
IEEE
13 years 12 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
JMLR
2010
134views more  JMLR 2010»
13 years 5 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
PKDD
2001
Springer
127views Data Mining» more  PKDD 2001»
14 years 3 months ago
Sentence Filtering for Information Extraction in Genomics, a Classification Problem
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...
Claire Nedellec, Mohamed Ould Abdel Vetah, Philipp...
ECML
2007
Springer
14 years 5 months ago
Using Text Mining and Link Analysis for Software Mining
Many data mining techniques are these days in use for ontology learning – text mining, Web mining, graph mining, link analysis, relational data mining, and so on. In the current ...
Miha Grcar, Marko Grobelnik, Dunja Mladenic
ALT
2002
Springer
14 years 7 months ago
Data Mining with Graphical Models
Abstract. The explosion of data stored in commercial or administrational databases calls for intelligent techniques to discover the patterns hidden in them and thus to exploit all ...
Rudolf Kruse, Christian Borgelt