Closed-world databases and circumscription
Artificial Intelligence
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Fast discovery of association rules
Advances in knowledge discovery and data mining
Integrating induction and abduction in logic programming
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on logical methods for computational intelligence
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Discovery of relational association rules
Relational Data Mining
Constraint-Based Rule Mining in Large, Dense Databases
Data Mining and Knowledge Discovery
Learning Logical Definitions from Relations
Machine Learning
The Induction of Rules for Predicting Chemical Carcinogenesis in Rodents
Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology
Involving Aggregate Functions in Multi-relational Search
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Carcinogenesis Predictions Using ILP
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Rule Evaluation Measures: A Unifying View
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
On Indefinite Databases and the Closed World Assumption
Proceedings of the 6th Conference on Automated Deduction
Aggregation-based feature invention and relational concept classes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning relational probability trees
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Prospects and challenges for multi-relational data mining
ACM SIGKDD Explorations Newsletter
CrossMine: Efficient Classification Across Multiple Database Relations
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
PRL: A probabilistic relational language
Machine Learning
Short communication: A new relational learning system using novel rule selection strategies
Knowledge-Based Systems
Introducing possibilistic logic in ILP for dealing with exceptions
Artificial Intelligence
Improving inductive logic programming by using simulated annealing
Information Sciences: an International Journal
An approach to mining the multi-relational imbalanced database
Expert Systems with Applications: An International Journal
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A new model of evaluating concept similarity
Knowledge-Based Systems
Real formal concept analysis based on grey-rough set theory
Knowledge-Based Systems
A phenotypic genetic algorithm for inductive logic programming
Expert Systems with Applications: An International Journal
ILP-based concept discovery in multi-relational data mining
Expert Systems with Applications: An International Journal
Analyzing Transitive Rules on a Hybrid Concept Discovery System
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Confidence-Based Concept Discovery in Relational Databases
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 04
The predictive toxicology evaluation challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Data mining in deductive databases using query flocks
Expert Systems with Applications: An International Journal
A creative abduction approach to scientific and knowledge discovery
Knowledge-Based Systems
Integrating neural networks and logistic regression to underpin hyper-heuristic search
Knowledge-Based Systems
Perceptually grounded self-diagnosis and self-repair of domain knowledge
Knowledge-Based Systems
Aggregating consistent endgame knowledge in Chinese Chess
Knowledge-Based Systems
Fitness function based on binding and recall rate for genetic inductive logic programming
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
A new relational Tri-training system with adaptive data editing for inductive logic programming
Knowledge-Based Systems
Type Extension Trees for feature construction and learning in relational domains
Artificial Intelligence
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Multi-relational data mining has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. Several relational knowledge discovery systems have been developed employing various search strategies, heuristics, language pattern limitations and hypothesis evaluation criteria, in order to cope with intractably large search space and to be able to generate high-quality patterns. In this work, we introduce an ILP-based concept discovery framework named Concept Rule Induction System (CRIS) which includes new approaches for search space pruning and new features, such as defining aggregate predicates and handling numeric attributes, for rule quality improvement. In CRIS, all target instances are considered together, which leads to construction of more descriptive rules for the concept. This property also makes it possible to use aggregate predicates more accurately in concept rule construction. Moreover, it facilitates construction of transitive rules. A set of experiments is conducted in order to evaluate the performance of proposed method in terms of accuracy and coverage.