LIMOS

DKQ 2011
Data and Knowledge Quality 2011
January 25, 2011

LRI IRISA
EGC 2011 -- Extraction et Gestion des Connaissances 2011
EGC 2011 -- Extraction et Gestion des Connaissances 2011

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After the success of the first six editions of the workshop Data and Knowledge Quality (QDC - Qualité des données et des connaissances) in conjunction with the French conference EGC in Paris (2005), in Lille (2006), in Namur (2007), in Nice (2008), in Strasbourg (2009),and in Hammamet Tunisia(2010), we propose to organize the seventh edition of the workshop in conjunction with EGC 2011 in Brest, France.
This workshop focuses on methods and techniques for analyzing and evaluating quality in the broad sense, both in data mining in knowledge management:

Knowledge discovery and decision making based on poor quality data (i.e., with errors, duplicates, inconsistencies, missing values, ...) have a direct and meaningful consequences to all users,analysts and decision makers, whatever the application domain, government, commercial, industrial or scientific. For this reason, the theme of data and knowledge quality has become a topic of interest in academia, in private/public research and also in the industry.

All applications dedicated to data analysis (such as text mining for example) require different forms of data preparation with many complex processing techniques, so that the input data conform to relatively "nice" distributions, containing no inconsistencies, duplicates, missing or incorrect values. But between the reality of available data and all the machinery for their analysis, a fairly large gap remains.

Ultimately, the evaluation and interpretation of the results of the analysis is usually performed by a specialist (expert of the domain, analyst, ...). The task of post-processing is often very time-consuming and a way to facilitate this task is to assist the specialist in providing decision criteria as measures of quality or measures of interest. These measures must be designed to combine two dimensions: one related to objective data quality, and the subjective ones related to the specialist.

Although the techniques used in data mining and knowledge management are very different, they share the goal of producing models of knowledge relevant to decision makers with a common concern for assessing the quality of the models produced. This workshop therefore relates to all areas involved in the Knowledge processing chain: data, discovery methods, and knowledge management.

We encourage submission of research papers and / or industrial case studies related to all aspects of data quality and quality of the methods for discovery and knowledge management in general. The duration of the workshop is a one-day dedicated to presentations of papers in the topics of interest listed on this page.


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