Inductive Logic Programming 6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers /
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...
Συγγραφή απο Οργανισμό/Αρχή: | |
---|---|
Άλλοι συγγραφείς: | |
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: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
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.