Using Background Knowledge to Build Multistrategy Learners
Machine Learning - Special issue on multistrategy learning
Hardness Results for Learning First-Order Representations and Programming by Demonstration
Machine Learning - Special issue on the ninth annual conference on computational theory (COLT '96)
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Learning for semantic interpretation: scaling up without dumbing down
Learning language in logic
Iterative part-of-speech tagging
Learning language in logic
A flexible learning system for wrapping tables and lists in HTML documents
Proceedings of the 11th international conference on World Wide Web
An introduction to inductive logic programming
Relational Data Mining
How to upgrade propositional learners to first order logic: case study
Relational Data Mining
Propositionalization approaches to relational data mining
Relational Data Mining
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
Machines that learn to play games
Challenges for Inductive Logic Programming
EPIA '99 Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Multi-relational Data Mining: a perspective
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Multi-Relational Data Mining, Using UML for ILP
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Learning in Clausal Logic: A Perspective on Inductive Logic Programming
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
Efficient Relational Learning from Sparse Data
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Inverse Entailment in Nonmonotonic Logic Programs
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Induction, Abduction, and Consequence-Finding
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Learning Logic Programs with Neural Networks
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Adaptive Bayesian Logic Programs
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Application of Pruning Techniques for Propositional Learning to Progol
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Learning Logic Models for Automated Text Categorization
AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Tailoring Representations to Different Requirements
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Handbook of data mining and knowledge discovery
Intelligent data analysis
Building large knowledge bases by mass collaboration
Proceedings of the 2nd international conference on Knowledge capture
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
A dynamic interaction between machine learning and the philosophy of science
Minds and Machines - Machine learning as experimental philosophy of science
Database dependency discovery: a machine learning approach
AI Communications
Nonmonotonic inductive logic programming by instance patterns
Proceedings of the 9th ACM SIGPLAN international conference on Principles and practice of declarative programming
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
First-Order Probabilistic Languages: Into the Unknown
Inductive Logic Programming
Proceedings of the 2005 conference on Multi-Relational Data Mining
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Acquisition of human feelings in music arrangement
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Java-based and secure learning agents for information retrieval in distributed systems
Information Sciences: an International Journal
Determination of general concept in learning default rules
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Learning in rich representations: inductive logic programming and computational scientific discovery
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Probabilistic inductive logic programming
Probabilistic inductive logic programming
Probabilistic inductive logic programming
Learning terminologies in probabilistic description logics
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Search-based design defects detection by example
FASE'11/ETAPS'11 Proceedings of the 14th international conference on Fundamental approaches to software engineering: part of the joint European conferences on theory and practice of software
Inductive logic programming by instance patterns
PADL'07 Proceedings of the 9th international conference on Practical Aspects of Declarative Languages
Multistrategy Operators for Relational Learning and Their Cooperation
Fundamenta Informaticae
Maintainability defects detection and correction: a multi-objective approach
Automated Software Engineering
What you like in design use to correct bad-smells
Software Quality Control
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From the Publisher:Inductive Logic Programming is a new research area situated in machine learning and logic programming, two subfields of artificial intelligence. The goal of inductive logic programming is to develop theories, techniques and tools for inducing hypotheses from observations using the representations from computational logic. Inductive Logic Programming has a high potential for applications in data mining, automated scientific discovery, knowledge discovery in databases, as well as automatic programming. This book provides a detailed state-of-the-art overview of Inductive Logic Programming as well as a collection of recent technical contributions to Inductive Logic Programming. The state-of-the-art overview is based on - among others - the succesful ESPRIT basic research project no. 6020 on Inductive Logic Programming, funded by the European Commission from 1992 till 1995. It highlights some of the most important recent results within Inductive Logic Programming and can be used as a thorough introduction to the field. This book is relevant to students, researchers and practitioners of artificial intelligence and computer science, especially those concerned with machine learning, data mining and computational logic.