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Third International Workshop on Third Generation Data Mining:

Towards Service-Oriented Knowledge Discovery (SoKD-2010)

The Workshop on Third Generation Data Mining: Towards Service-Oriented Knowledge Discovery (SoKD-2010) will be held on 24 September 2010 in Barcelona, Spain, in conjunction with the 21st European Conference on Machine Learning and the 14th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-2010). SoKD-2010 is the third workshop on this topic:

The first SoKD 2008 Workshop (see proceedings) was organized at ECML/PKDD-2008 in September 2008 in Antwerp, Belgium.
The second SoKD 2009 Workshop (see proceedings) was organized at ECML/PKDD-2009 in September 2009 in Bled, Slovenia.

Background

A major challenge for third generation data mining and knowledge discovery systems is the integration of distributed data/knowledge resources (which are highly diverse in nature in terms of representation and data formats) and computer systems (tools for data integration, data mining and knowledge discovery). First generation data mining systems supported a single algorithm or a small collection of algorithms that are designed to mine attribute-valued data. Today's second generation systems support high performance interfaces to databases and data warehouses, and provide increased scalability and increased functionality; for example, second generation systems can mine larger and more complex data sets and provide increased flexibility by supporting a data mining schema and a data mining query language.

The emerging third generation data mining and knowledge discovery systems should be able to mine distributed and highly heterogeneous data found on intranets/extranets/grid/cloud and integrate efficiently with operational data/knowledge management and data mining systems. The key technologies which will make third generation data mining and knowledge discovery possible should include:

meta-data (semantic annotations) on different information resources (data, human-coded knowledge, and machine-induced patterns and predictive models), and on the ingredients of data mining and knowledge discovery systems (pattern mining and model discovery tools),
implementations of data mining and knowledge discovery tools as services available on the web. Such service-oriented data mining and knowledge discovery systems will enable meta-level search of data/knowledge resources and mining systems, facilitating the construction of knowledge discovery workflows (representing potentially repeatable sequences of data mining and data integration steps) and resulting in improved pattern and model discovery.

Compared to contemporary search engines which provide a means of locating data on the net, third generation data mining and knowledge discovery systems will provide a means for discovering patterns, associations, changes and anomalies in networked data, where each data source comes with its own structure, semantics, data formats, names, concepts, and access methods. Currently, the burden falls on the user to manually (via programs) convert between the data formats, resolve conflicts, integrate data and interpret results in order to make viable use of this information.

Goals and Target Audience

This workshop intends to gather contributions supporting third generation data mining and knowledge discovery, elaborating a service-oriented approach to information fusion, for the needs of exploratory data analysis in the framework of inductive databases, enriched with ontology information available from the web.

Given the growing amount of information available on the net, this workshop should be of interest to knowledge engineers, as well as students and researchers interested in data mining and advanced methods for knowledge discovery. The workshop will also concern researchers in databases and in software engineering, for whom data mining is an “application area”. Finally, it will not fail to attract researchers and practitioners in semantic web technologies, as the ultimate fulfillment of a truly semantic web resides in the possibility of extracting not just readily available information but also deep knowledge in the form of underlying patterns and regularities.

Topics

Theoretical framework for third generation data mining and knowledge discovery

Inductive databases, constraint-based data mining and inductive queries

Service-oriented approaches to data mining

Meta-level annotations and search for data mining services

Multiple-source learning or learning from heterogeneous data including text & images

Integrating prior knowledge (probabilities, ontologies) into data mining

Data mining ontologies, in particular novel ontological representation schemes for handling quantitative data and data streams

Data mining workflows/scenarios

Data mining on the grid and cloud computing

Applications of service-oriented data mining approaches in business, ecological modeling, medicine, health care, e-science, bioinformatics, etc.

Submission

Authors are invited to submit papers related to the topics listed above. Technical papers will be assessed based on relevance, originality, significance, technical soundness and clarity of presentation, by at least 2 Program Committee members.

The maximum length of submissions is 12 pages for technical papers and 6 pages for position papers. All submissions should follow the Springer-Verlag LNCS format. Please submit papers as PDF files to the EasyChair SoKD-10 home page.

Workshop Program

View Workshop Program or download PDF version

Workshop Proceedings

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Organization

Workshop Chairs

Melanie Hilario

Artificial Intelligence Laboratory, University of Geneva

melanie[dot]hilario[at]unige[dot]ch

Joost N. Kok

Leiden Institute of Advanced Computer Science, Leiden University

joost[at]liacs[dot]nl

Nada Lavrac

Department of Knowledge Technologies, Jozef Stefan Institute

nada[dot]lavrac[at]ijs[dot]si

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