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|Title=The 8th International Symposium on Intelligent Data Analysis | |Title=The 8th International Symposium on Intelligent Data Analysis | ||
|Type=Conference | |Type=Conference | ||
| − | | | + | |Official Website=http://ida09.liris.cnrs.fr |
| − | |||
|City=Lyon | |City=Lyon | ||
| − | |Country= | + | |Country=Country:FR |
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|wikicfpId=3675 | |wikicfpId=3675 | ||
|pageCreator=127.0.0.1 | |pageCreator=127.0.0.1 | ||
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|Start Date=Aug 31, 2009 | |Start Date=Aug 31, 2009 | ||
|End Date=Sep 2, 2009 | |End Date=Sep 2, 2009 | ||
| + | |Academic Field=Artificial Intelligence | ||
| + | |Event Status=as scheduled | ||
| + | |Event Mode=on site | ||
}} | }} | ||
| + | {{Event Deadline | ||
| + | |Notification Deadline=May 7, 2009 | ||
| + | |Camera-Ready Deadline=May 28, 2009 | ||
| + | |Submission Deadline=Mar 30, 2009 | ||
| + | }} | ||
| + | {{S Event}} | ||
<pre> | <pre> | ||
Latest revision as of 15:22, 19 October 2022
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Venue
Lyon, France
Warning: Venue is missing. The map might not show the exact location.
Over the past decade, there has been a growing body of literature on the understanding of data analysis processes. Making smart use of the increasingly sophisticated analysis algorithms requires much expert knowledge to be part of the process itself, often in an interactive way. This knowledge is at least partially integrated into more complex data analysis meta methods and modeling scenarios that haven proven beneficial. In addition to the more traditional algorithmic or application oriented submissions, IDA2009 especially encourages submissions of papers addressing this emerging trend at the cross roads of traditional data analysis methods, complex data analysis scenarios and interactive tools that assist the analyst throughout the process. We are interested in papers describing methods that aid the analyst in the analysis procedure and we are also looking for contributions abstracting or formalizing the often interactive data analysis process. Contributions describing methods should highlight potential insights into the data, the presented method offers.
Examples of Scenarios describing steps from data to interesting models are:
* Abstractions, such as generic workflows,
* Formalizations, such as data analysis "design patterns",
* User Participation, such as interactive systems, and
* Approaches to Benchmarking of Data Analysis Scenarios.
Methods can stem from, but are not limited to, the areas of Machine Learning, Statistics, Data Mining, Artificial Intelligence, and (Interactive) Visualization. The proceedings of IDA 2009 will appear in the prestigious Lecture Notes in Computer Science series by Springer.
30 March 2009 Submission due
7 May 2009 Notification of acceptance
28 May 2009 Camera-ready copy due
This CfP was obtained from WikiCFP
