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ILP 2015 : The 25th International Conference on Inductive Logic Programming

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Conference Series : Inductive Logic Programming
 
Link: http://ilp2015.jp/
 
When Aug 20, 2015 - Aug 22, 2015
Where Kyoto, Japan
Abstract Registration Due Apr 19, 2015
Submission Deadline Apr 24, 2015
Notification Due Jun 1, 2015
Categories    artificial intelligence   machine learning   logic programming   inductive reasoning
 

Call For Papers

The 25th International Conference on Inductive Logic Programming (ILP 2015) will be held in Kyoto, Japan, August 20th - 22nd. The ILP conference is the premier international forum on logic-based and relational learning. Originally focused on induction of logic programs, it has broadened its scope and attracted a lot of attention and interest in recent years.

Authors are invited to submit papers presenting original results on all aspects of learning in logic, multi-relational learning and data mining, statistical relational learning, graph and tree mining, relational reinforcement learning, connections with other learning paradigms, and learning in other logic-based knowledge representation frameworks.

Typical, but not exclusive, topics of interest for submissions include:

- Theoretical aspects: logical foundations, learning scenarios, data/model representation frameworks, computational and/or statistical properties, etc.

- Algorithms: logical, probabilistic and statistical approaches, distance and kernel-based methods, learning with (semi)structured data, supervised/unsupervised/semi-supervised relational learning, relational reinforcement learning, inductive databases, link discovery, new propositionalization approaches, multi-instance learning, predicate invention, learning dynamics of systems, etc.

- Representations and languages for logic-based learning: including datalog, first-order logic, description logics and ontologies, higher-order logic, probabilistic logical representations, mapping between alternative representations.

- Systems: systems that implement inductive logic programming algorithms with special emphasis on issues like optimization, parallelism, efficiency and scalability.

- Applications including, but not restricted to multi-relational learning from structured (e.g., labeled graphs, tree patterns) and semi-structured data (e.g., XML documents), learning from relational data in areas of science (bioinformatics, cheminformatics, medical informatics, social science, etc.), natural language processing (computational linguistics, text/web mining etc.), engineering, robotics, games, semantic web, social networks, the arts, etc.

We solicit three kinds of papers:

1) Long papers describing original mature work containing appropriate experimental evaluation and/or representing a self-contained theoretical contribution. Long papers will be reviewed by at least 3 members of the program committee. Authors will be notified prior to the conference on acceptance/rejection for the Springer LNAI post-conference proceedings. Authors of accepted papers will be assigned a standard time slot for presentation.

2) Short papers describing original work in progress, brief accounts of original ideas without conclusive experimental evaluation, and other relevant work of potentially high scientific interest but not yet qualifying for the long paper category. The PC chairs will accept/reject short papers on the grounds of relevance. Authors of accepted short papers will be assigned a reduced time slot for presentation. Each short paper will be reviewed by at least 3 members of the program committee on the basis of both the manuscript and its presentation, and the authors of selected papers will be invited to submit a long version for the Springer LNAI post-conference proceedings; In this case, the long paper will be reviewed again by the assigned PC members of the short paper and be finally accepted if satisfactorily addressing the reviewer's requirements.

3) Papers relevant to the conference topics and recently published or 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. The PC chairs will accept/reject such papers on the grounds of relevance and quality of the original publication venue. Authors of accepted papers will be assigned a reduced time slot for presentation. These papers will not appear in the Springer LNAI post-conference proceedings.

SUBMISSION:

Submissions in category 1 or 2 must not have been published or be under review for a journal or for another conference with published proceedings. They should be submitted in the Springer LNCS format. Long (short) papers must not exceed 12 (6) pages. The indicated number of pages includes the title page, references and figures. Submissions must be formatted according to the Springer LNCS author instructions,
http://www.springer.com/comp/lncs/Authors.html
Papers in category 3 should be submitted in their original format and the authors should indicate the original publication venue. All Paper submissions will be electronic through the ILP 2015 easychair site:
https://www.easychair.org/conferences/?conf=ilp2015

A special issue of the Machine Learning journal is planned following the conference, which is open for everyone. This special issue welcomes conference submissions from all the three categories above, which should be significantly revised and extended to meet the MLJ criteria, for re-reviewing by the PC.

ASSOCIATED EVENTS:

MLSS 2015 Kyoto – Machine Learning Summer School 2015 in Kyoto – will be held on August 24 – September 5, 2015, in Kyoto University.

IMPORTANT DATES:

* Long paper submission: May 4, 2015
* Long Paper notification: June 1, 2015
* Short Paper submission: June 26, 2015
* Short Paper notification: July 1, 2015

CONFERENCE AND PROGRAM CO-CHAIRS:

Katsumi Inoue, NII
Hayato Ohwada, Tokyo University of Science
Akihiro Yamamoto, Kyoto University

PUBLICITY CHAIR:

Kotaro Okazaki, SONAR

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