Inductive Logic Programming 6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Muggleton, Stephen (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1997.
• Έκδοση: 1st ed. 1997.
• Σειρά: Lecture Notes in Artificial Intelligence ; 1314
• Θέματα: Architecture, Computer.; Software engineering.; Artificial intelligence.; Computer programming.; Computer System Implementation.; Software Engineering/Programming and Operating Systems.; Artificial Intelligence.; Programming Techniques.

This book constitutes the strictly refereed post-workshop proceedings of the 6th International Workshop on Inductive Logic Programming, ILP-96, held in Stockholm, Sweden, in August 1996. The 21 full papers were carefully reviewed and selected for inclusion in the book in revised version. Also includ...

Πίνακας περιεχομένων:

• Inductive logic programming for natural language processing
• An initial experiment into stereochemistry-based drug design using inductive logic programming
• Applying ILP to diterpene structure elucidation from 13C NMR spectra
• Analysis and prediction of piano performances using inductive logic programming
• Noise detection and elimination applied to noise handling in a KRK chess endgame
• Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes
• Polynomial-time learning in logic programming and constraint logic programming
• Analyzing and learning ECG waveforms
• Learning rules that classify ocular fundus images for glaucoma diagnosis
• A new design and implementation of progol by bottom-up computation
• Inductive logic program synthesis with DIALOGS
• Relational knowledge discovery in databases
• Efficient ?-subsumption based on graph algorithms
• Integrity constraints in ILP using a Monte Carlo approach
• Restructuring chain datalog programs
• Top-down induction of logic programs from incomplete samples
• Least generalizations under implication
• Efficient proof encoding
• Learning Logic programs with random classification noise
• Handling Quantifiers in ILP
• Learning from positive data
• ?-Subsumption and its application to learning from positive-only examples.