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» Learning Classifiers from Semantically Heterogeneous Data
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ALT
2004
Springer
14 years 5 months ago
Learning Languages from Positive Data and Negative Counterexamples
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the ...
Sanjay Jain, Efim B. Kinber
KDD
1994
ACM
98views Data Mining» more  KDD 1994»
14 years 27 days ago
Rule Induction for Semantic Query Optimization
Semantic query optimization can dramatically speed up database query answering by knowledge intensive reformulation. But the problem of how to learn required semantic rules has no...
Chun-Nan Hsu, Craig A. Knoblock
BMCBI
2010
171views more  BMCBI 2010»
13 years 9 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
KESAMSTA
2010
Springer
14 years 1 months ago
Classifying Agent Behaviour through Relational Sequential Patterns
Abstract. In Multi-Agent System, observing other agents and modelling their behaviour represents an essential task: agents must be able to quickly adapt to the environment and infe...
Grazia Bombini, Nicola Di Mauro, Stefano Ferilli, ...
ALT
2010
Springer
13 years 10 months ago
Contrast Pattern Mining and Its Application for Building Robust Classifiers
: The ability to distinguish, differentiate and contrast between different data sets is a key objective in data mining. Such ability can assist domain experts to understand their d...
Kotagiri Ramamohanarao