Probabilistic Inductive Logic Programming Theory and Applications /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Raedt, Luc De (Επιμελητής έκδοσης), Frasconi, Paolo (Επιμελητής έκδοσης), Kersting, Kristian (Επιμελητής έκδοσης), Muggleton, Stephen (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Lecture Notes in Computer Science, 4911
• Θέματα: Computer science.; Computer programming.; Algorithms.; Mathematical logic.; 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.

Πίνακας περιεχομένων:

• 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.