Call for Paper Conference

In conjunction with the 2009 IEEE International Conference on Data Mining (ICDM 2009)
Miami, USA, December 6 - 9, 2009

http://sadm09.isti.cnr.it

Knowledge Discovery is generally described as a process for the automatic extraction of interesting, useful, and previously unknown knowledge from data. It is expected that data characteristics, data semantics as well as the knowledge that already exists about the data can be directly incorporated into the knowledge discovery process. However, semantic and reasoning aspects may intervene in several steps of the discovery process, and now the question is how these aspects interact within the process and the forms that this can take. In data pre-processing, semantic aspects may help in (1) identifying source data of interest, (2) enriching the data with additional domain information, and (3) generating more meaningful and human understandable patterns, once the generated patterns are directly related to the input data. During the mining task, semantics may be used as constraints, thus allowing (1) search space reduction, (2) pattern pruning, and (3) the development of more efficient algorithms. Background knowledge may intervene in the post-processing step helping in the explanation of large amounts of patterns, typically difficult to interpret. The objective of SADM is to introduce methods which can explicitly consider data semantics, background knowledge, or reasoning in the mining process. This knowledge has to be represented/formalized in a knowledge repository, such as ontologies, conceptual schemas, knowledge bases, etc. The main aspect is that this knowledge has to be explicitly incorporated into the KDD process, where the algorithms for data preprocessing, data mining or post-processing make use of this knowledge to improve the KDD process. The key idea is to develop a more general understanding about how to exploit data semantics and background knowledge, and to create standardized procedures for designing more intelligent data mining methods. We believe that such an effort can lead to the development of the science of semantic data mining.

* Journal Special Issue*
The selected Best Paper will be recommended for publication in a special issue of Knowledge and Information Systems (KAIS) journal edited by Springer..

* Topics of Interest*:
The workshop will seek submissions where semantic information plays an explicit role in the knowledge discovery process. The intent of the workshop is to bring together researchers and practitioners interested in semantic aspects in data mining from a wide range of possible data mining subareas, including: web mining, medical data mining, spatio-temporal data mining, ubiquitous knowledge discovery, and privacy-preserving data mining.

The aim of the workshop is to receive contributions in the following topics, which are not exclusive:

* Techniques to embed semantics into the discovery process
* Semantics in data pre-processing and post-processing
* Semantic-based pruning
* Knowledge-based data mining algorithms
* Semantic-based techniques for feature selection
* Ontologies and data pre-processing
* Ontology-based evaluation of discovered patterns
* Data mining query languages
* Constraint-based data mining
* Semantics for Knowledge representation, interpretation, and reasoning
* Semantics in spatial and spatio-temporal data mining
* Conceptual modeling and data mining
* Semantic-based KDD processes and frameworks
* Semantics in biological data mining
* Semantics for uncertainty handling in data mining
* Semantics in privacy-preserving data mining
* Semantics in social network data mining

* Important Dates*:
* July 17, 2009 Due date for full workshop papers
* September 8, 2009 : Notification of paper acceptance to authors
* September 28, 2009 : Camera-ready of accepted papers
* December 6, 2009 : Workshop date

*Preliminary Program Committee List *(***to be completed***):
* Luis Otavio Alvares, Universidade Federal do Rio Grande do Sul, Brazil
* Ronnie Alves, Institute of Developmental Biology and Cancer, Faculte des Sciences, France
* Miriam Baglioni, Department of Computer Science, University of Pisa, Italy
* Jean-Francois Boulicaut, INSA, University of Lyon, France
* Toon Calders, Eindhoven Technical University, The Netherlands
* Ivan Janciak, University of Wien, Austria
* Jose Antonio Fernandes de Macedo, EPFL, Switzerland
* Donato Malerba, University of Bari, Italy
* Giuseppe Manco, ICAR CNR, Cosenza, Italy
* Vipin Kumar, University of Minnesota, USA
* Stanley Oliveira, Embrapa Informatica - São Paulo, Brazil
* Solange Rezende, Universidade Federal de São Carlos, Brazil
* Giuseppe Psaila, University of Bergamo, Italy
* Yannis Theodoridis, University of Pireus, Greece
* Monica Wachowicz, Wageningen University, The Netherland
* Mohammed Zaki, Rensselaer Polytechnic Institute, USA

Submission Guidelines and Review Process:
High quality research papers in the relevant areas are solicited. Original papers exploring new directions will receive especially careful consideration. Papers that have already been accepted or are currently under review for other conferences or journals will not be considered. All accepted workshop papers will be included in the IEEE ICDM Workshop Proceedings,
to be published by the IEEE Computer Society Press. Therefore, at least one author of the accepted paper must register to attend the workshop. Paper submissions should be limited to a maximum of 8 pages in PDF format, in the IEEE 2-column style (see the IEEE Computer Society Press Proceedings Author Guidelines at http://www.computer.org/portal/pages/cscps/cps/final/icdm06.xml).
All papers will be reviewed by the Program Committee on the basis of technical quality, relevance to workshop topics, originality, significance, and clarity. We will follow the double blind review process. Authors must hence not use identifying information in the text of the paper and bibliographies must be referenced to preserve anonymity. Please use the Submission Form on the ICDM'09 website to submit your paper.