Relational Data Mining
Multi-relational Decision Tree Induction
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Propositionalisation and Aggregates
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Rule Evaluation Measures: A Unifying View
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Transformation-Based Learning Using Multirelational Aggregation
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Subgroup Discovery with CN2-SD
The Journal of Machine Learning Research
ReMauve: A Relational Model Tree Learner
Inductive Logic Programming
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
Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Estimating and bounding aggregations in databases with referential integrity errors
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
A Comparison between Neural Network Methods for Learning Aggregate Functions
DS '08 Proceedings of the 11th International Conference on Discovery Science
ILP-based concept discovery in multi-relational data mining
Expert Systems with Applications: An International Journal
A multi-relational approach to spatial classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 2005 conference on Multi-Relational Data Mining
Extended aggregations for databases with referential integrity issues
Data & Knowledge Engineering
Refining aggregate conditions in relational learning
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Classifying relational data with neural networks
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Transforming graph data for statistical relational learning
Journal of Artificial Intelligence Research
Learning in the presence of large fluctuations: a study of aggregation and correlation
NFMCP'12 Proceedings of the First international conference on New Frontiers in Mining Complex Patterns
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The fact that data is scattered over many tables causes many problems in the practice of data mining. To deal with this problem, one either constructs a single table by propositionalisation, or uses a Multi-Relational Data Mining algorithm. In either case, one has to deal with the non-determinacy of one-to-many relationships. In propositionali-sation, aggregate functions have already proven to be powerful tools to handle this non-determinacy. In this paper we show how aggregate functions can be incorporated in the dynamic construction of patterns of Multi-Relational Data Mining