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https://ceur-ws.org/Vol-611/foreword.pdf
Foreword
Large amounts of data increasingly becoming available and described using real-
life ontologies represented in Semantic Web languages, recently opened up the
possibility for interesting real-world data mining applications on the Semantic
Web. However, exploiting this global resource of data requires new kinds of ap-
proaches for data mining and data analysis that would be able to deal at the
same time with its scale and with the complexity, expressiveness, and hetero-
geneity of the representation languages, leverage on availability of ontologies
and explicit semantics of the resources, and account for novel assumptions (e.g.,
”open world”) that underlie reasoning services within the Semantic Web.
The workshop tried to address the above issues, in particular focusing on
the problems of how machine learning techniques, such as statistical learning
methods and inductive forms of reasoning, can work directly on the richly struc-
tured Semantic Web data and exploit the Semantic Web technologies, what is
the value added of machine learning methods for the Semantic Web, and what
are the challenges for developers of machine learning techniques for the Semantic
Web data, for example in the area of ontology mining.
The workshop was meant to bring together researchers and practitioners
interested in the interdisciplinary research on the intersection of the Semantic
Web with Knowledge Discovery and Machine Learning, and provide a meeting
point for the related communities to stimulate collaboration and enable cross-
fertilization of ideas.
Specifically, the review phase produced a selection of 5 full papers, 1 position
paper, and 2 late breaking news abstracts. IRMLeS 2010 program was further
enriched by two invited talks from prominent researchers. Dr Melanie Hilario
presented in her talk an ongoing research on optimizing the knowledge discov-
ery process through the semantic meta-mining, involving background ontology
representing the domain of data mining. Professor Steffen Staab demonstrated
in his talk how the enrichment of Web 2.0 data by automatically discovered se-
mantic relationships may improve the user experience. The workshop was also
successful in terms of registrations and attendance.
The topics covered by IRMLeS 2010 included: ontology learning, and semantic
tagging to expose the semantics of unstructured or semi-structured data as text,
or Web 2.0 tags; management, and retrieval of Semantic Web resources, e.g.
RDF data; probabilistic approaches; similarity measures for ontological data;
inductive reasoning with ontologies; finally using ontologies, and other formal
representations as background knowledge to steer whole knowledge discovery
process.
In the final wrap-up discussion, a number of open problems and promising
directions were elicited. Similarly as the last year, the topic of integration of
induction and deduction has been recognized as essential for the Semantic Web,
to deal with real, noisy data. Related to this topic, the topics of probabilistic
approaches, and uncertain inference over semantic resources were discussed. The
need for new metrics for evaluating the output of machine learning methods in
the Semantic Web setting was recognized, especially in the context of the open
world assumption. The novel topic of semantic data mining also gained attention
during discussion, and a call for gathering the community of people working on
ontologies/another KR formats for representing data mining domain has been
issued. Some other new tasks have also been identified as an interesting future
direction of research on machine learning for the Semantic Web that include:
ontology repair, and instance matching (especially in the context of a lack of
unique name assumption on the Semantic Web).
Given such open issues and the success of the two first editions, we plan to
organize next edition in the near future.
Acknowledgments The workshop chairs are grateful to all the people who
contributed to the event from the program committee members to the additional
reviewers, the presenters and the participants. A special thank is due to the
invited speakers who shared their vision on the topics of the workshop. Finally,
we are grateful also to the ESWC 2010 Workshop Chairs, Program Chairs and
General Chair for their constant support.
Heraklion, May 31, 2010
Claudia d’Amato
Nicola Fanizzi
Marko Grobelnik
Agnieszka Lawrynowicz
Vojtěch Svátek
Program Committee Members
– Sarabjot S. Anand – University of Warwick
– Bettina Berendt – Katholieke Universiteit Leuven
– Abraham Bernstein – University of Zurich
– Floriana Esposito – University of Bari
– Mohand-Said Hacid – University Lyon 1
– Melanie Hilario – University of Geneva
– Andreas Hotho – University of Kassel
– Jose Iria – IBM Research, Zurich
– Ross D. King – University of Aberystwyth
– Jens Lehmann – University of Leipzig
– Francesca A. Lisi – University of Bari
– Thomas Lukasiewicz – Oxford University
– Matthias Nickles – University of Bath
– Sebastian Rudolph – University of Karlsruhe
– Jetendr Shamdasani – University of the West of England
– Steffen Staab – University of Koblenz-Landau
– Umberto Straccia – ISTI-CNR, Pisa
– Volker Tresp – Siemens, Munich
Additional Reviewers
Jörg-Uwe Kietz – University of Zurich
Workshop Homepage
http://irmles.di.uniba.it/2010/