Probabilistic Inductive Logic Programming Theory and Applications / [electronic resource] :
edited by Luc Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton.
- Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
- VIII, 341 p. online resource.
- Lecture Notes in Computer Science, 4911 0302-9743 ; .
- Lecture Notes in Computer Science, 4911 .
Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP( ): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis.
9783540786528
10.1007/978-3-540-78652-8 doi
Computer science.
Computer software.
Data mining.
Artificial intelligence.
Bioinformatics.
Computer Science.
Artificial Intelligence (incl. Robotics).
Programming Techniques.
Mathematical Logic and Formal Languages.
Algorithm Analysis and Problem Complexity.
Data Mining and Knowledge Discovery.
Computational Biology/Bioinformatics.
Q334-342 TJ210.2-211.495
006.3
Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP( ): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis.
9783540786528
10.1007/978-3-540-78652-8 doi
Computer science.
Computer software.
Data mining.
Artificial intelligence.
Bioinformatics.
Computer Science.
Artificial Intelligence (incl. Robotics).
Programming Techniques.
Mathematical Logic and Formal Languages.
Algorithm Analysis and Problem Complexity.
Data Mining and Knowledge Discovery.
Computational Biology/Bioinformatics.
Q334-342 TJ210.2-211.495
006.3