Know 2015 - Fourth International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know@LOD 2015)

Fourth International Workshop on
Knowledge Discovery and Data Mining Meets Linked Open Data
(Know-AT-LOD 2015)
Co-located with the 11th Extended Semantic Web Conference (ESWC 2015)
May 31 - June 4, Portoroz, Slovenia
http://knowalod2015.informatik.uni-mannheim.de
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The fourth international workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know-AT-LOD) will be held at the 12th Extended Semantic Web Conference (ESWC).
Knowledge discovery and data mining (KDD) is a well-established field with a large community investigating methods for the discovery of patterns and regularities in large data sets, including relational databases and unstructured text. Research in this field has led to the development of practically relevant and scalable approaches such as association rule mining, subgroup discovery, graph mining, and clustering. At the same time, the Web of Data has grown to one of the largest publicly available collections of structured, cross-domain data sets. While the growing success of Linked Data and its use in applications, e.g., in the e-Government area, has provided numerous novel opportunities, its scale and heterogeneity is posing challenges to the field of knowledge discovery and data mining.
Contributions from the knowledge discovery field may help foster the future growth of Linked Open Data. Some recent works on statistical schema induction, mapping, and link mining have already shown that there is a fruitful intersection of both fields. With the proposed workshop, we want to investigate possible synergies between both the Linked Data community and the field of Knowledge Discovery, and to explore novel directions for mutual research. We wish to stimulate a discussion about how state-of-the-art algorithms for knowledge discovery and data mining could be adapted to fit the characteristics of Linked Data, such as its distributed nature, incompleteness (i.e., absence of negative examples), and identify concrete use cases and applications.
Submissions have to be formatted according to the Springer LNCS guidelines. We welcome both full papers (max 12 pages) as well as work-in-progress and position papers (max 6 pages). Accepted papers will be published online via CEUR-WS, with a selection of the best papers of each ESWC workshop appearing in an additional volume edited by Springer. Papers must be submitted online via Easychair at https://easychair.org/conferences/?conf=knowlod201....
Topics of interest include data mining and knowledge discovery methods for generating and processing, or using linked data, such as
- Automatic link discovery
- Event detection and pattern discovery
- Frequent pattern analysis
- Graph mining
- Knowledge base debugging, cleaning and repair
- Large-scale information extraction
- Learning and refinement of ontologies
- Modeling provenance information
- Ontology matching and object reconciliation
- Scalable machine learning
- Statistical relational learning
Important Dates:
Submission deadline: March 16th, 2015
Notification: April 3rd, 2015
Camera ready version: April 17th, 2015
Workshop: May 31st or June 1st, 2015
Organization:
Jens Lehmann, University of Leipzig, Germany
Heiko Paulheim, University of Mannheim, Germany
Vojtěch Svátek, University of Economics, Prague, Czech Republic
Johanna Völker, University of Mannheim, Germany