Inductive Logic Programming (ILP) is a subfield of machine learning, focusing on learning logical representations from relational data. The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data, multi-relational learning and data mining. Originally focusing on the induction of logic programs, over the years it has expanded its research horizon significantly and welcomes contributions to all aspects of learning in logic, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

Call for Papers

We solicit submissions in all areas of learning in logic and multi-relational data mining. Areas of interest include, but are not limited to:

    Theory of ILP, foundations of logical & relational learning, computational learning theory.
    Learning in various logical representations and formalisms, such as logic programming & answer set programming, first-order & higher-order logic, description logic & ontologies.
    Statistical relational learning, including structure/parameter learning for probabilistic logic languages, relational probabilistic graphical models, kernel-based methods, neural- symbolic learning.
    Meta-interpretative learning & predicate invention.
    Semi-supervised & unsupervised relational learning.
    Methods for scaling-up ILP, parallel & distributed relational learning.
    Incremental & online relational learning, learning from data streams.
    Applications of ILP.

We solicit three types of submissions:

    Conference papers, describing original work with appropriate experimental evaluation and/or a self-contained theoretical contribution. Submitted conference papers should not have been published, or be under review for a journal, or another conference with published proceedings. Conference papers may be either long papers, of up to 15 pages, including references, of short papers of up to 6-9 pages, including references. Long papers should contain a substantial contribution that justifies their length, e.g. proofs of extensive experimental studies. Accepted conference papers will be published by the Springer LNAI conference proceedings.
    Late-breaking abstracts, briefly outlining novel ideas and proposals that the authors would like to present at the conference. These could include e.g. original work in progress without conclusive experimental findings, or other relevant work, not yet ready for publication. Submissions of late-breaking abstracts will be accepted/rejected on the grounds of relevance. Accepted late-breaking abstracts will be published on the conference website. Late-breaking abstracts must not exceed 4 pages, including references.
    Recently published papers relevant to ILP, or papers recently accepted for publication by a first-class conference such as ECML/PKDD, ICML, KDD, ICDM, AAAI, IJCAI, etc. or journal such as MLJ, DMKD, JMLR etc. These will be accepted/rejected on the grounds of relevance and quality of the original publication venue. For papers of this category a link to the original work will be published on the conference website. Authors should submit the abstract and the PDF file of the original submission, specifying in the abstract the original venue where the papar was accepted in addition to the acceptance date. Authors submitting a recently published paper should submit it through IJCLR's "Recently Published Papers Track" option from the submission page.

All accepted papers will be assigned a presentation slot at the conference. Long conference papers will be assigned an extended slot, while short conference papers, late-breaking abstracts and recently published papers will be assigned a reduced slot.

Additionally, authors of accepted papers will have the opportunity to present their papers during the joint poster sessions. At least one of the authors of accepted papers/late-breaking abstracts must register for the conference and present their work.