[PlanetKR] International Conference on Inductive Logic Programming, 2016 - Call For Papers

Russo, Alessandra M a.russo at imperial.ac.uk
Mon Dec 14 04:33:50 EST 2015


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CALL FOR PAPERS
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ILP 2016: The 26th International Conference on Inductive Logic Programming

	4th - 6th September, 2016
	
	London, UK

	http://ilp16.doc.ic.ac.uk
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The 26th International Conference on Inductive Logic Programming (ILP 2016) will be held in London, UK, September 4th - 6th, 2016. It will be held at the "Warren House Conference Centre", situated next to Richmond Park (UK Nature Reserve and the largest London Royal Park) and well connected to the centre of London via tubes and trains.

The ILP conference series is the premier international forum for learning from structured relational data. 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, multi-relational data mining, 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.

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

- Theoretical aspects: logical-foundations of learning; computational/statistical learning theory; specialisation and generalisation; probabilistic logic-based learning; graph and tree mining.
- Representation and languages for learning: logic programming; Datalog;first-order logic; description logic and ontologies; higher-order logic; Answer Set Programming; probabilistic logic languages; constraint logic programming; knowledge graphs.
- Algorithms and systems: learning with (semi-)structured data; (semi-)supervised and unsupervised relational learning; relational reinforcement learning; predicate invention; propositionalisation approaches; multi-instance learning; learning in the presence of uncertainty; meta-level learning.
- Applications of learning in: art; bioinformatics; systems biology; games; medical informatics; robotics; natural language processing; web-mining; software engineering; modelling and adaptation of control systems; socio-technical systems.

In addition to the above topics, ILP 2016 is also encouraging contributions in the areas of cognitive technologies, knowledge acquisition from big data, the cloud and crowd sourced data, deep relational learning, as well as contributions on the application of any of these solutions to real world problems. 

The conference will host keynote talks from both industry and academia and will run the first International ILP Competition.

We solicit three types of submissions: 

1) Long papers describing original mature work containing appropriate experimental evaluation and/or representing a self-contained theoretical contribution. Accepted long paper submissions will be assigned a standard time slot for presentation and will appear in the Springer LNAI post-conference proceedings. If a long paper submission is not accepted as a long paper, it may be accepted as a "short paper" (see next paragraph), in which case it will be assigned a reduced time slot for presentation, and the authors may be given the opportunity to submit a revised version that will be reviewed after the conference for possible inclusion in the Springer LNAI post-conference proceedings.

2) Short papers describing original work in progress, brief accounts of original ideas without conclusive evaluation, and other relevant work of potentially high scientific interest but not yet qualifying for the long paper category. They will be accepted/rejected on the grounds of their relevance. Accepted short papers will be assigned a reduced time slot for presentation. Authors of selected papers will be invited to submit a long version that will be reviewed after the conference for possible inclusion in the Springer LNAI post-conference proceedings.

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. These will be accepted/rejected 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.


IMPORTANT DATES:
* Abstract registration:       7 May   2016 
* Long paper submission:      13 May   2016 
* Long Paper notification:    26 June  2016 
* Short Paper submission:     24 July  2016 
* Short Paper notification:   28 July  2016 

SUBMISSION:

Submissions of long papers and short papers must not have been published or be under review for a journal or for another conference with published proceedings. Submissions must be in Springer LNAI format, according to the Springer LNCS author instructions (http://www.springer.com/comp/lncs/Authors.html).
 
Long papers must not exceed 12 pages including references; short papers must not exceed 6 pages not including references. 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 2016 Easychair site: 

https://easychair.org/conferences/?conf=ilp2016

The post-proceedings from the Conference will be published by LNAI Springer. 

We expect there will be a special issue of the Machine Learning Journal following the conference, which will be open for everyone. This special issue will welcome conference submissions from all three categories, which should be significantly revised and extended, to meet the MLJ criteria, and will be re-reviewed by PC members.

CONFERENCE AND PROGRAM CO-CHAIRS: 
Alessandra Russo, Imperial College London UK 
James Cussens, University of York, UK 

ILP COMPETITION CHAIR:
Mark Law, Imperial College London, UK

PUBLICITY CHAIR: 
Krysia Broda, Imperial College London, UK

ASSOCIATED EVENT:
3rd International Workshop on Probabilistic Logic Programming



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