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Evento: 'Machine Learning Journal special issue cfp : Inductive Logic Programming and Multi-Relational Learning'

Call for Papers
Divulgação de "Call for Papers".
Data: Friday, November 15, 2013 At 08:00
Duração: Todo dia

Call for Papers - MLJ Special Issue Papers


On the ocasion of the ILP'13 Conference, we are delighted to issue an open call for a Machine Learning Journal special issue on Inductive Logic Programming and related work on Multi-Relational learning.
Typical, but not exclusive, topics of interest for submissions include:

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

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

- 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, etc.), natural language processing (computational linguistics, text and web mining etc.), engineering, games, semantic web, the arts, etc.

The special issue will also include selected papers from the ILP'13 Conference.

The submission deadline is

Nov 15, 2013

The submission system for Machine Learning can be found on:


An article is submitted to the ILP'13 special number by choosing 'ILP 2013' as the article type.
Articles must adhere to all requirements of the Machine Learning Journal, and should be at most 20 pages long. Submissions exceeding this length will not be given priority during reviewing and may, as a consequence, be under review for a longer period. We strive for notification within 8 weeks although we cannot guarantee it.

The Special Number Editors
Gerson Zaverucha, UFRJ, Brazil
Vítor Santos Costa, UP, Portugal

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