2nd Linked Data Mining Challenge at Know@LOD / ESWC 2014

Call for Challenge Participation: 2nd Linked Data Mining Challenge
organized in connection with the Know@LOD 2014 workshop at ESWC 2014, May
25, Crete, Greece
http://knowalod2014.informatik.uni-mannheim.de/en/linked-data-mining-challenge/

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Submission dates (other dates available from the website):
31 March 2014: Submission deadline for predictive task results
3 April 2014: Submission deadline for LDMC papers
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The Linked Data Mining Challenge (LDMC) will consist of two tracks, each
with a different domain and dataset. It is possible to participate in a
single track or in both tracks.

Track A addresses linked government data, more specifically, the public
procurement domain. Data from this domain are frequently analyzed by
investigative journalists and ‘transparency watchdog’ organizations; these,
however, 1) rely on interactive tools such as OLAP and spreadsheets,
incapable of spotting hidden patterns, and 2) only deal with isolated
datasets, thus ignoring the potential of interlinking to external datasets.
LDMC could possibly initiate a paradigm shift in analytical processing of
this kind of data, eventually leading to large-scale benefits to the
citizenship. It is also likely to spur the research collaboration between
the Semantic Web community (represented by the linked data sub-community as
its practice-oriented segment) and the Data Mining community.

Track B addresses the domain of scientific research collaboration, in
particular cross-disciplinary collaboration. While collaboration between
people within the same community often emerges naturally, many possible
cross-disciplinary collaborations never form due to a lack of awareness of
cross-boundary synergies. Finding meaningful patterns in collaborations can
help revealing potential cross-disciplinary collaborations that might
otherwise have remained hidden.

Each track requires the participants to download a real-world RDF dataset
and accomplish at least one pre-defined task on it using their own or
publicly available data mining tool. The tracks involve 1 predictive and 2
exploratory data mining tasks in total.
Partial mapping to external datasets is also available, which allows for
extraction of further features from the Linked Open Data cloud in order to
augment the core dataset.
The best participant in each track will be awarded. The ranking of the
participants will be made by the LDMC evaluation panels, and will take into
account both the quality of the submitted LDMC paper and the prediction
quality measure in the predictive task (Track A only, if addressed by the
participant).

More detail on the datasets, tasks, results/paper submission and evaluation
is in
http://knowalod2014.informatik.uni-mannheim.de/en/linked-data-mining-challenge/

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Contact persons:
Track A:
    Vojtěch Svátek, University of Economics, Prague
    Jindřich Mynarz, University of Economics, Prague
Track B:
    Heiko Paulheim, University of Mannheim, Germany

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Vojtech Svatek, University of Economics, Prague
Nam.W.Churchilla 4, 13067 Praha 3, CZECH REPUBLIC
phone: +420 224095495, e-mail: svatek@vse.cz
web: http://nb.vse.cz/~svatek