This book constitutes the refereed proceedings of the 6th International Conference on Discovery Science, DS 2003, held in Sapporo, Japan in October 2003.

The 18 revised full papers and 29 revised short papers presented together with 3 invited papers and abstracts of 2 invited talks were carefully reviewed and selected from 80 submissions. The papers address all current issues in discovery science including substructure discovery, Web navigation patterns discovery, graph-based induction, time series data analysis, rough sets, genetic algorithms, clustering, genome analysis, chaining patterns, association rule mining, classification, content based filtering, bioinformatics, case-based reasoning, text mining, Web data analysis, and more.

The13thInternationalConferenceonInductive LogicProgramming(ILP 2003), organizedbytheDepartmentofInformaticsattheUniversityofSzeged,washeld between September 29 and October 1, 2003 in Szeged, Hungary. ILP 2003 was co-located with the Kalm' ar Workshop on Logic and Computer Science devoted to the workofL' aszl'oKalm' arandto recentresultsinlogicandcomputerscience. This volume contains all full papers presented at ILP 2003, together with the abstracts of the invited lectures by Ross D. King (University of Wales, Aber- twyth) and John W. Lloyd (Australian National University, Canberra). TheILP conferenceseries,startedin1991,wasoriginallydesignedto provide an international forum for the presentation and discussion of the latest research resultsinallareasoflearninglogicprograms.InrecentyearsthescopeofILPhas been broadened to cover theoretical, algorithmic, empirical, and applicational aspects of learning in non-propositional logic, multi-relational learning and data mining, and learning from structured and semi-structured data. The program committee received altogether 58 submissions in response to the call for papers, of which 5 were withdrawn by the authors themselves. Out of the remaining 53 submissions, the program committee selected 23 papers for full presentation at ILP 2003. High reviewing standards were applied for the selection of the papers. For the ?rst time, the "Machine Learning" journal awarded the best student papers. The awards were presented to Marta Arias for her theoretical paper withRoniKhardon:ComplexityParametersforFirst-OrderClasses,andtoKurt DriessensandThomasG.. artnerfortheirjointalgorithmicpaperwithJanRamon: Graph Kernels and Gaussian Processes for Relational Reinforcement Learning.

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.

This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILP 2015, held in Kyoto, Japan, in August 2015. The 14 revised papers presented were carefully reviewed and selected from 44 submissions. The papers focus on topics such as theories, algorithms, representations and languages, systems and applications of ILP, and cover all areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining, relational reinforcement learning, graph mining, connections with other learning paradigms, among others.