ILP 2007, the 17th Conference on Inductive Logic Programming, was held in Corvallis, Oregon, USA, June 19-21, and was collocated with the 24th Inter- tional Conferenceon Machine Learning.The programconsisted of 15 full and 14 short presentations, a poster session, keynote talks by Paolo Frasconi (Learning withKernelsandLogicalRepresentations)andDavidJensen(BeyondPrediction: Directions for Probabilistic and Relational Learning), and several joint sessions with ICML. Thirty-eight submissions were received this year, out of which ?fteen were accepted for publication in the proceedings as full papers and eleven as short papers.Inclusionin the proceedings was decided bytaking into accountnotonly the relevance and quality of the work described, but also the quality and level of maturityofthetext.Severalmoresubmissionswereacceptedaswork-in-progress presentations. Thus the 2007 edition of ILP continued the tradition of adopting high selectivity for published papers, while at the same time o?ering a forum for work in progress. All accepted papers were made available in temporary online proceedings during the conference. Revised versions of the submitted papers, incorporating feedback from discussions at the conference, are included either in the proce- ings of the conference (this volume) or, for a small number of selected papers, in a special issue of theMachine Learning journal (abstracts of these are included in this volume). Papers reporting on work in progress remain available in the online proceedings, athttp: //pages.cs.wisc.edu/ shavlik/ilp07wip/

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Conference on Inductive Logic Programming, ILP 2014, held in Nancy, France, in September 2014. The 14 revised papers presented were carefully reviewed and selected from 41 submissions. The papers focus on topics such as the inducing of logic programs, learning from data represented with logic, multi-relational machine learning, learning from graphs, and applications of these techniques to important problems in fields like bioinformatics, medicine, and text mining.