Clausal Discovery

Authors:
Luc De Raedt;Luc Dehaspe
Affiliations:
Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium/ E-mail: luc.deraedt@cs.kuleuven.ac.be, luc.dehaspe@cs.kuleuven.ac.be;Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium/ E-mail: luc.deraedt@cs.kuleuven.ac.be, luc.dehaspe@cs.kuleuven.ac.be
Venue:
Machine Learning - special issue on inductive logic programming
Year:
1997

Citing 26
Cited 82

Programming in Prolog (2nd ed.)

Programming in Prolog (2nd ed.)
Prolog programming for artificial intelligence

Prolog programming for artificial intelligence
Logical foundations of artificial intelligence

Logical foundations of artificial intelligence
Foundations of logic programming; (2nd extended ed.)

Foundations of logic programming; (2nd extended ed.)
Induction as nonmonotonic inference

Proceedings of the first international conference on Principles of knowledge representation and reasoning
Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A theory and methodology of inductive learning

Readings in knowledge acquisition and learning
Using the m-estimate in rule induction

Journal of Computing and Information Technology
Existence and nonexistence of complete refinement operators

ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Flattening and Saturation: Two Representation Changes for Generalization

Machine Learning - Special issue on evaluating and changing representation
Grammatically biased learning: learning logic programs using an explicit antecedent description language

Artificial Intelligence
First-order jk-clausal theories are PAC-learnable

Artificial Intelligence
Declarative Bias for Specific-to-General ILP Systems

Machine Learning - Special issue on bias evaluation and selection
Theories for mutagenicity: a study in first-order and feature-based induction

Artificial Intelligence - Special volume on empirical methods
Advances in knowledge discovery and data mining

Advances in knowledge discovery and data mining
Inductive logic programming and knowledge discovery in databases

Advances in knowledge discovery and data mining
Explora: a multipattern and multistrategy discovery assistant

Advances in knowledge discovery and data mining
Inductive Logic Programming: Techniques and Applications

Inductive Logic Programming: Techniques and Applications
Learning Logical Definitions from Relations

Machine Learning
The CN2 Induction Algorithm

Machine Learning
Predicate Invention in Inductive Data Engineering

ECML '93 Proceedings of the European Conference on Machine Learning
DLAB: A Declarative Language Bias Formalism

ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
Inductive Constraint Logic

ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Normal Forms for Inductive Logic Programming

ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
SATCHMO: A Theorem Prover Implemented in Prolog

Proceedings of the 9th International Conference on Automated Deduction
Inductive Learning Applied to Program Construction and Verification

AIFIPP '92 Extended Papers from the IFIP TC12 Workshop on Artificial Intelligence from the Information Processing Perspective: Knowledge Oriented Software Design

Levelwise Search and Pruning Strategies for First-Order HypothesisSpaces

Journal of Intelligent Information Systems - Special issue on methodologies for intelligent information systems
An introduction to inductive logic programming

Relational Data Mining
Inductive logic programming for knowedge discovery in databases

Relational Data Mining
Three companions for data mining in first order logic

Relational Data Mining
How to upgrade propositional learners to first order logic: case study

Relational Data Mining
Editorial

Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns

Data Mining and Knowledge Discovery
Scaling Up Inductive Logic Programming by Learning from Interpretations

Data Mining and Knowledge Discovery
A KDD framework to support database audit

Information Technology and Management
Confirmation-Guided Discovery of First-Order Rules with Tertius

Machine Learning
Challenges for Inductive Logic Programming

EPIA '99 Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
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
Machine Learning for Data Mining in Medicine

AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Inductive Verification and Validation of the KULRoT RoboCup Team

RoboCup-98: Robot Soccer World Cup II
How to Upgrade Propositional Learners to First Order Logic: A Case Study

Machine Learning and Its Applications, Advanced Lectures
Scalability Issues in Inductive Logic Programming

ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms

ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
A Logical Database Mining Query Language

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
Towards Combining Inductive Logic Programming with Bayesian Networks

ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Specific-to-general learning for temporal events

Eighteenth national conference on Artificial intelligence
Data mining tasks and methods: Rule discovery: inductive logic programming approaches

Handbook of data mining and knowledge discovery
Probabilistic logic learning

ACM SIGKDD Explorations Newsletter
Inducing Multi-Level Association Rules from Multiple Relations

Machine Learning
Subgroup Discovery with CN2-SD

The Journal of Machine Learning Research
Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned

Machine Learning
Relational sequential inference with reliable observations

ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning the structure of Markov logic networks

ICML '05 Proceedings of the 22nd international conference on Machine learning
Markov logic networks

Machine Learning
Propositionalization-based relational subgroup discovery with RSD

Machine Learning
Mathematical applications of inductive logic programming

Machine Learning
Learning Recursive Theories in the Normal ILP Setting

Fundamenta Informaticae
Sequential inference with reliable observations: learning to construct force-dynamic models

Artificial Intelligence
Inference of abduction theories for handling incompleteness in first-order learning

Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Building rules on top of ontologies for the semantic web with inductive logic programming

Theory and Practice of Logic Programming
I-extended databases

MMACTEE'08 Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering
Efficient and Scalable Induction of Logic Programs Using a Deductive Database System

Inductive Logic Programming
Boosting Descriptive ILP for Predictive Learning in Bioinformatics

Inductive Logic Programming
Discriminative Structure Learning of Markov Logic Networks

ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Just Add Weights: Markov Logic for the Semantic Web

Uncertainty Reasoning for the Semantic Web I
Towards Machine Learning on the Semantic Web

Uncertainty Reasoning for the Semantic Web I
CSM-SD: Methodology for contrast set mining through subgroup discovery

Journal of Biomedical Informatics
An Inductive Logic Programming Approach to Statistical Relational Learning

Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
Structure Learning of Markov Logic Networks through Iterated Local Search

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Brave induction: a logical framework for learning from incomplete information

Machine Learning
Discriminative training of Markov logic networks

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Integrating explanatory and descriptive learning in ILP

IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Improving the efficiency of inductive logic programming through the use of query packs

Journal of Artificial Intelligence Research
Specific-to-general learning for temporal events with application to learning event definitions from video

Journal of Artificial Intelligence Research
Expert-guided subgroup discovery: methodology and application

Journal of Artificial Intelligence Research
On mining closed sets in multi-relational data

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A simple-transition model for relational sequences

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Sequential inference with reliable observations: Learning to construct force-dynamic models

Artificial Intelligence
Automated conjecture making in number theory using HR, Otter and Maple

Journal of Symbolic Computation
Towards a general framework for data mining

KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Applying inductive logic programming to process mining

ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Markov logic

Probabilistic inductive logic programming
Basic principles of learning Bayesian logic programs

Probabilistic inductive logic programming
RedTrees: A relational decision tree algorithm in streams

Expert Systems with Applications: An International Journal
Inductive logic programming in databases: From datalog to $\mathcal{dl}+log}^{\neg\vee}$

Theory and Practice of Logic Programming
Probabilistic declarative process mining

KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Towards clausal discovery for stream mining

ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Generative Structure Learning for Markov Logic Networks

Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Boosting learning and inference in Markov logic through metaheuristics

Applied Intelligence
Outlier detection in relational data: A case study in geographical information systems

Expert Systems with Applications: An International Journal
Predictive and descriptive approaches to learning game rules from vision data

IBERAMIA-SBIA'06 Proceedings of the 2nd international joint conference, and Proceedings of the 10th Ibero-American Conference on AI 18th Brazilian conference on Advances in Artificial Intelligence
Learning models of relational stochastic processes

ECML'05 Proceedings of the 16th European conference on Machine Learning
Local patterns: theory and practice of constraint-based relational subgroup discovery

LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
A survey on statistical relational learning

AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Learning rules from multisource data for cardiac monitoring

AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Automatic induction of abduction and abstraction theories from observations

ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Inductive equivalence of logic programs

ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
CLASSIC'CL: an integrated ILP system

DS'05 Proceedings of the 8th international conference on Discovery Science
Principles of inductive reasoning on the semantic web: a framework for learning in AL-log

PPSWR'05 Proceedings of the Third international conference on Principles and Practice of Semantic Web Reasoning
Active subgroup mining: a case study in coronary heart disease risk group detection

Artificial Intelligence in Medicine
MC-TopLog: complete multi-clause learning guided by a top theory

ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Contrast mining from interesting subgroups

Bisociative Knowledge Discovery
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
Learning Recursive Theories in the Normal ILP Setting

Fundamenta Informaticae
Comparing and evaluating approaches to probabilistic reasoning: theory, implementation, and applications

Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
Mining closed patterns in relational, graph and network data

Annals of Mathematics and Artificial Intelligence

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Abstract

The clausal discovery engine claudien is presented. CLAUDIEN is an inductive logic programming enginethat fits in the descriptive data mining paradigm. CLAUDIEN addressescharacteristic induction from interpretations, a task which is relatedto existing formalisations of induction in logic.In characteristic induction from interpretations,the regularities are represented by clausal theories,and the data using Herbrand interpretations.Because CLAUDIEN uses clausal logicto represent hypotheses, the regularities inducedtypically involve multiple relations or predicates.CLAUDIEN also employs a novel declarative bias mechanismto define the set of clauses that may appear in a hypothesis.