Appel: LD4KD, Linked Data for Knowledge Discovery Workshop at ECML/PKDD

[Thierry Hamon]

Date: Fri, 11 Apr 2014 09:39:02 +0100
From: Mathieu d'Aquin <m.daquin at open.ac.uk>
Message-ID: <5347AA26.1080007 at open.ac.uk>
X-url: http://events.kmi.open.ac.uk/ld4kd2014/
X-url: http://www.ecmlpkdd2014.org/


** apologies for cross-posting **

================================
LD4KD 2014
1st Workshop on Linked Data for Knowledge Discovery

http://events.kmi.open.ac.uk/ld4kd2014/

co-located with the European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery 2014 (ECML/PKDD 2014)
15-19 September 2014, Nancy, France (http://www.ecmlpkdd2014.org/ )

================================

Linked Data have attracted a lot of attention in recent years in many
research areas, as their technologies and principles provide new ways to
overcome typical data management and consumption issues such as
reliability, heterogeneity, provenance or completeness. However, the way
in which Linked Data can be applicable and beneficial to the Knowledge
Discovery (KDD) pocess is still not completely understood. Many aspects
of KDD could benefit from Linked Data, e.g. mining Linked Data sources,
using Linked Data to enrich, represent or integrate local data for data
preparation, interpretation or visualisation.

LD4KD will be an interactive hub to explore the benefits of Linked Data
principles and technologies for Knowledge Discovery, together with
addressing the new challenges that will emere from joining the two
fields. It will be an opportunity for practitioners of both fields to
create communication and collaboration channels,and bridge the gap
between their overlapping, but mostly isolated communities.

The workshop encourages the participation of researchers from the
Knowledge Discovery field to discuss and get informed about the use,
benefits and challenges of Linked Data, while th Linked Data researchers
can take advantage of and adapt Knowledge Discovery methods in their
domain.

*SCOPE*

We welcome high quality position and research papers in which (1) Linked
Data are used as support of Knowledge Discovery processes to extract
useful knowledge, or (2) Knowledge Discovery techniques are adapted to
work and possibly extend Linked Data.

Topics of either theoretical and applied interest include, but are not
limited to:

- Linked Data for data pre-processing: cleaning, sorting, filtering or
  enrichment
- Linked Data applied to Machine Learning
- Linked Data for pattern extraction and behaviour detection
- Linked Data for pattern interpretation, visualization or optimisation
- Reasoning with patterns and Linked Data
- Reasoning on and extracting knowledge from Linked Data
- Linked Data mining
- Links prediction or links discovery using KDD
- Graph mining in Linked Data
- Interacting with Linked Data for Knowledge Discovery

*IMPORTANT DATES*

Paper submission deadline: June 20th
Notification Of Acceptance: July 20th
Camera ready copies due: August 5th, 2014
Workshop date: September 15th/19th, 2014

*SUBMISSIONS*

Articles should be written following the Springer LNCS template (see
authors instructions at
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0) and can be
up to 10 pages in lenght for research papers or 5 pages for position
papers, including figures and references.

Submissions are exclusively admitted electronically, in PDF format,
through the EasyChair system. The submission site is
https://www.easychair.org/conferences/?conf=ld4kd

* ORGANISING COMMITTEE *

Ilaria Tiddi, Knowledge Media Institute, The Open University, UK
Mathieu d'Aquin, Knowledge Media Institute, The Open University, UK
Nicolas Jay, Orpailleur, Loria, France

*CONTACTS*

mathieu.daquin at open.ac.uk
ilaria.tiddi at open.ac.uk
nicolas.jay at loria.fr

*PROGRAMME COMMITTEE*

Francesca Alessandra
Claudia D'Amato
Tommaso di Noia
Nicola Fanizzi
Johannes Fürnkranz
Nathalie Hernandez
Agnieszka Lawrynowicz
Amedeo Napoli
Andriy Nikolov
Heiko Paulheim
Sebastian Rudolph
Harald Sack
Vojtěch Svátek
Isabelle Tellier
Cassia Trojahn

-- The Open University is incorporated by Royal Charter (RC 000391), an
   exempt charity in England & Wales and a charity registered in
   Scotland (SC 038302).

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