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====== The Semantic Data Mining (SEDAMI) Workshop ====== | ====== The Semantic Data Mining (SEDAMI) Workshop ====== | ||
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+ | **SEDAMI webapge is [[http:// | ||
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+ | The theme of the SEDAMI workshop is semantic data mining. With this workshop we aim to get an insight into the current status of research in this area. We focus mainly on methods that allow include/ | ||
+ | We encourage contributions on methods, techniques and applications that are both domain-specific but also transversal to different application domains. In particular, we solicit contributions that aim to focus on semantic data mining for providing and/or enhancing interpretability, | ||
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+ | The 2nd edition of SEDAMI will be co-located with the [[https:// | ||
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+ | The [[start2021|1st edition of SEDAMI]] was co-located with [[https:// | ||
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+ | ====== SEDAMI 2023 at ECAI 2023 ====== | ||
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+ | ====== Program ====== | ||
+ | * The workshop will take place on Sunday, October 1st | ||
+ | * Location: [[https:// | ||
+ | * Session starts at 9:00, see [[https:// | ||
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+ | ===== Schedule ===== | ||
+ | ^Time^Accepted paper^ | ||
+ | | 09:00 - 09:10 | Introduction to the workshop | | ||
+ | | 09:10 - 09:30 | Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks \\ //Yunming Hui, Melisachew Wudage Chekol and Shihan Wang// | | ||
+ | | 09:30 - 09:50 | Visual patterns in an interactive app for analysis based on control charts and SHAP values \\ //Iwona Grabska-Gradzińska, | ||
+ | | 09:50 - 10:10 | Improving understandability of explanations with a usage of expert knowledge \\ //Maciej Szelążek, Szymon Bobek and Grzegorz J. Nalepa// | | ||
+ | | 10:10 - 10:30 | Post–Mining on Association Rule Bases \\ //Dietmar Seipel, Marcel Waleska, Daniel Weidner, Sven Rausch and Martin Atzmueller// | ||
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+ | **Organising committee** | ||
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+ | * Szymon Bobek, | ||
+ | * Martin Atzmueller, | ||
+ | * Nada Lavrac, Jožef Stefan Institute, Slovenia | ||
+ | |||
+ | ===== Important dates===== | ||
+ | * **Submission Deadline:** 31.07.2023 | ||
+ | * **Notification of Acceptance: | ||
+ | * **Camera-Ready Versions Due:** < | ||
+ | * **Workshop date:** 30 September - 1 October 2023 | ||
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+ | ===== Call for papers ===== | ||
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+ | * Full CFP: {{ : | ||
+ | * One-pager: {{ : | ||
+ | ===== Aims and Scope ===== | ||
+ | The general goal of data mining is to uncover novel, interesting, | ||
+ | Thus, recent advances of data mining and machine learning apparently bring new challenges in its practical use in data mining, including interpretability, | ||
+ | Using semantic information such as domain/ | ||
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+ | The aim of this workshop, is to get an insight into the current status of research in semantic data mining, showing how to include/ | ||
+ | |||
+ | We encourage contributions on methods, techniques and applications that are both domain-specific but also transversal to different application domains. In particular, we solicit contributions that aim to focus on semantic data mining for providing and/or enhancing interpretability, | ||
+ | |||
+ | ===== Topics of interest ===== | ||
+ | |||
+ | Overall, we are interested in receiving papers related to the following | ||
+ | topics which include but are not limited to: | ||
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+ | * Introduction of semantics into the data mining process | ||
+ | * Explainable artificial intelligence and domain knowledge | ||
+ | * Declarative domain knowledge | ||
+ | * Declarative data mining | ||
+ | * Declarative explainable artificial intelligence | ||
+ | * Integration of causal machine learning and expert knowledge | ||
+ | * Neuro-symbolic artificial intelligence | ||
+ | * Knowledge modeling and data mining | ||
+ | * Feature engineering for transparency and explanation | ||
+ | * Knowledge-based data mining approaches | ||
+ | * Knowledge-graphs in data mining | ||
+ | * Interpretable models in data mining | ||
+ | * Role of explanations in data mining | ||
+ | * Inductive logic programming and data mining | ||
+ | * Transparent and hybrid models in data mining | ||
+ | * Human in the loop of the data mining process | ||
+ | * Role of Linked Open Data in data mining | ||
+ | * Applications of all of the above | ||
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+ | |||
+ | ===== Program Committee (tentative) ===== | ||
+ | * Sören Auer, Leibniz University of Hannover & TIB, Germany | ||
+ | * Klaus-Dieter Althoff, University of Hildesheim & DFKI, Germany | ||
+ | * Przemysław Biecek, Warsaw University of Technology, Poland | ||
+ | * Johannes Fürnkranz, Johannes Kepler University Linz, Austria | ||
+ | * João Gama, University of Porto, Portugal | ||
+ | * Kristian Kersting, TU Darmstadt, Germany | ||
+ | * Stan Matwin, Dalhousie University, Canada | ||
+ | * Sławomir Nowaczyk, Halmstad University, Sweden | ||
+ | * Jose Palma, Universidad de Murcia, Spain | ||
+ | * Mykola Pechenizkyi, | ||
+ | * Marc Plantevit, Université Lyon, France | ||
+ | * Eric Postma, Tilburg University, The Netherlands | ||
+ | * Céline Rouveirol, Université Sorbonne Paris Nord, France | ||
+ | * Ute Schmid, University of Bamberg, Germany | ||
+ | * Marek Sikora, Silesian University of Technology, Poland | ||
+ | * Dietmar Seipel, University of Würzburg, Germany | ||
+ | * Blaž Škrlj, Jožef Stefan Institute, Slovenia | ||
+ | * Jerzy Stefanowski, | ||
+ | * Stefano Teso, KU Leuven, Belgium | ||
+ | * Gerhard Weikum, Max Planck Institute for Informatics, | ||
+ | * Filip Železny, CTU, Prague, Czech Republic | ||
+ | * Agnieszka Ławrynowicz, | ||
+ | * Weronika T. Adrian, AGH UST, Krakow, Poland | ||
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+ | ===== Submission details ===== | ||
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+ | {{: | ||
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+ | Please submit papers using the dedicated [[https:// | ||
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+ | Furthermore, | ||
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+ | All submitted papers must: | ||
+ | * be written in English; | ||
+ | * contain author names, affiliations, | ||
+ | * be formatted according to the [[https:// | ||
+ | * be in PDF (make sure that the PDF can be viewed on any platform). | ||
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