Expert systems: tools and applications
Expert systems: tools and applications
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Experimental comparison of human and machine learning formalisms
Proceedings of the sixth international workshop on Machine learning
The Utility of Knowledge in Inductive Learning
Machine Learning
Knowledge discovery in databases: an overview
AI Magazine
Compression, significance and accuracy
ML92 Proceedings of the ninth international workshop on Machine learning
Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
Algorithmic Program DeBugging
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Knowledge Acquisition from Structured Data: Using Determinate Literals to Assist Search
IEEE Expert: Intelligent Systems and Their Applications
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Machine Learning
Learning Nonrecursive Definitions of Relations with LINUS
EWSL '91 Proceedings of the European Working Session on Machine Learning
Rule Induction with CN2: Some Recent Improvements
EWSL '91 Proceedings of the European Working Session on Machine Learning
Peepholing: Choosing Attributes Efficiently for Megainduction
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
Background Knowledge and Declarative Bias in Inductive Concept Learning
AII '92 Proceedings of the International Workshop on Analogical and Inductive Inference
Understanding the Crucial Role of AttributeInteraction in Data Mining
Artificial Intelligence Review
IEEE Transactions on Knowledge and Data Engineering
Distributed mining of classification rules
Knowledge and Information Systems
Learning semantic functions of attribute grammars
Nordic Journal of Computing
Systems for Knowledge Discovery in Databases
IEEE Transactions on Knowledge and Data Engineering
Application of Different Learning Methods to Hungarian Part-of-Speech Tagging
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Combining Multiple Interrelated Streams for Incremental Clustering
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Learning recursive functions from noisy examples using generic genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
Most current applications of inductive learning in databases take place in the context of a single extensional relation. The authors place inductive learning in the context of a set of relations defined either extensionally or intentionally in the framework of deductive databases. LINUS, an inductive logic programming system that induces virtual relations from example positive and negative tuples and already defined relations in a deductive database, is presented. Based on the idea of transforming the problem of learning relations to attribute-value form, several attribute-value learning systems are incorporated. As the latter handle noisy data successfully, LINUS is able to learn relations from real-life noisy databases. The use of LINUS for learning virtual relations is illustrated, and a study of its performance on noisy data is presented.