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sedami:start [2021/04/01 07:33] sbksedami:start [2023/09/29 06:57] (current) – [Schedule] sbk
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 ====== The Semantic Data Mining (SEDAMI) Workshop ====== ====== The Semantic Data Mining (SEDAMI) Workshop ======
 +
 +**SEDAMI webapge is [[http://sedami.geist.re]]**
  
 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/utilize/exploit semantic information and domain knowledge in the context of machine learning and data mining, focusing on domains and research questions that have not been deeply investigated so far and to improve solutions to classic tasks. 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/utilize/exploit semantic information and domain knowledge in the context of machine learning and data mining, focusing on domains and research questions that have not been deeply investigated so far and to improve solutions to classic tasks.
 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, the introduction and preservation of knowledge, as well as the provisioning of explanations. 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, the introduction and preservation of knowledge, as well as the provisioning of explanations.
  
 +The 2nd edition of SEDAMI will be co-located with the [[https://ecai2023.eu/|26th European Conference on Artificial Intelligence (ECAI 2023)]].
  
-====== SEDAMI 2021 at IJCAI 2021 ======+The [[start2021|1st edition of SEDAMI]] was co-located with [[https://ijcai-21.org/|30th International Joint Conference on Artificial Intelligence (IJCAI-21)]] see [[https://ceur-ws.org/Vol-3032/|CEUR-WS Vol-3032]]. 
 + 
 + 
 +====== SEDAMI 2023 at ECAI 2023 ====== 
 + 
 +====== Program ====== 
 +  * The workshop will take place on Sunday, October 1st  
 +  * Location: [[https://maps.app.goo.gl/A4VV2HTryfdaa5E36|WMI]],  Room: [[https://intra.matinf.uj.edu.pl/plan/| 0086]] 
 +  * Session starts at 9:00, see [[https://ecai2023.eu/acceptedworkshops|ECAI Program]] 
 + 
 +===== Schedule ===== 
 +The presentation should be around 15 minutes with 5 minutes for questions. 
 +The total time reserved from one presentation is 20 minutes. 
 + 
 +^Time^Accepted paper^ 
 +| 09:00 - 09:10 | Introduction to the workshop | 
 +| 09:10 - 09:30 | Visual patterns in an interactive app for analysis based on control charts and SHAP values \\ //Iwona Grabska-Gradzińska, Maciej Szelążek, Szymon Bobek and Grzegorz J. Nalepa // | 
 +| 09:30 - 09:50 | Improving understandability of explanations with a usage of expert knowledge \\ //Maciej Szelążek, Szymon Bobek and Grzegorz J. Nalepa// | 
 +| 09:50 - 10:20 | Post–Mining on Association Rule Bases \\ //Dietmar Seipel, Marcel Waleska, Daniel Weidner, Sven Rausch and Martin Atzmueller//
 +| 10:20 - 10:30 | Leveraging Graph Embedding for Opinion Leader Detection in Dynamic Social Networks \\ //Yunming Hui, Melisachew Wudage Chekol and Shihan Wang// | 
 + 
 + 
 + 
 +**Organising committee** 
 + 
 +  * Szymon Bobek,  Jagiellonian University 
 +  * Martin Atzmueller,  Osnabrück University & German Research Center for AI (DFKI), Germany, 
 +  * Nada Lavrac, Jožef Stefan Institute, Slovenia 
 + 
 +====Important dates===== 
 +  * **Submission Deadline:** 31.07.2023 
 +  * **Notification of Acceptance:** <del>14.08.2023</del>16.08.2023 
 +  * **Camera-Ready Versions Due:** <del>21.08.2023</del>11.09.2023 
 +  * **Workshop date:** 30 September - 1 October 2023
  
  
 ===== Call for papers ===== ===== Call for papers =====
  
-{{ :sedami:sedami2021-cfp.pdf |Call For Papers -- SEDAMI 2021}} +  * Full CFP: {{ :sedami:sedami2023-cfp.pdf |Call for papers}} 
-===== Motivation for the workshop =====+  * One-pager: {{ :sedami:sedami2023-cfp-one-pager.pdf | Call for papers}} 
 +===== Aims and Scope =====
 The general goal of data mining is to uncover novel, interesting, and ultimately understandable patterns, cf. (Fayyad 1996), i.e., relating to valuable, useful and implicit knowledge. Looking at the development of data mining in the last decades, it can be observed that not only the data mining tasks used to be more restricted, but also the applied data mining workflows were simpler. The general goal of data mining is to uncover novel, interesting, and ultimately understandable patterns, cf. (Fayyad 1996), i.e., relating to valuable, useful and implicit knowledge. Looking at the development of data mining in the last decades, it can be observed that not only the data mining tasks used to be more restricted, but also the applied data mining workflows were simpler.
 Thus, recent advances of data mining and machine learning apparently bring new challenges in its practical use in data mining, including interpretability, introduction and preservation of knowledge, as well as the provisioning of explanations. Thus, recent advances of data mining and machine learning apparently bring new challenges in its practical use in data mining, including interpretability, introduction and preservation of knowledge, as well as the provisioning of explanations.
 Using semantic information such as domain/background knowledge in data mining is a promising emerging direction for addressing these problems, where the knowledge is typically represented in a knowledge repository, such as an ontology, or a knowledge base. The main aspect of semantic data mining, which we focus on in this workshop, is the explicit integration of this knowledge into the data mining and knowledge discovery modeling step, where the algorithms for data mining/modeling or post-processing make use of the formalized knowledge to improve the overall results. Using semantic information such as domain/background knowledge in data mining is a promising emerging direction for addressing these problems, where the knowledge is typically represented in a knowledge repository, such as an ontology, or a knowledge base. The main aspect of semantic data mining, which we focus on in this workshop, is the explicit integration of this knowledge into the data mining and knowledge discovery modeling step, where the algorithms for data mining/modeling or post-processing make use of the formalized knowledge to improve the overall results.
 +
 +The aim of this workshop, is to get an insight into the current status of research in semantic data mining, showing how to include/utilize/exploit semantic information and domain knowledge in the context of machine learning and data mining, focussing on domains and research questions that have not been deeply investigated so far and to improve solutions to classic tasks.
 +
 +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, the introduction and preservation of knowledge, as well as the provisioning of explanations - thus addressing important principles, methods, tools and future research directions in this emerging field.
  
 ===== Topics of interest ===== ===== Topics of interest =====
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   * Introduction of semantics into the data mining process   * Introduction of semantics into the data mining process
 +  * Explainable artificial intelligence and domain knowledge
   * Declarative domain knowledge   * Declarative domain knowledge
   * Declarative data mining   * Declarative data mining
-  * Knowledge modelling and 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   * Feature engineering for transparency and explanation
   * Knowledge-based data mining approaches   * Knowledge-based data mining approaches
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   * Applications of all of the above   * Applications of all of the above
  
-===== Workshop format ===== 
-We are aiming at the 0.5-day workshop that includes regular paper presentations of peer reviewed research papers (10-12 pages including references), as well as peer-reviewed short or position papers (5-6 pages including references). Furthermore, we encourage tool presentations. Depending on the number of submissions, long papers will be 20-30 minutes and short papers 15-20 minutes including Q&A. For the workshop we are expecting around 20-30 participants to attend. Should IJCAI 2021 be held online because of the COVID-19 situation, then we are willing to hold the workshop online. 
  
 +===== 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, TU Eindhoven, The Netherlands
 +  * 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, Poznan University of Technology, Poland
 +  * Stefano Teso, KU Leuven, Belgium
 +  * Gerhard Weikum, Max Planck Institute for Informatics, Germany
 +  * Filip Železny, CTU, Prague, Czech Republic
 +  * Agnieszka Ławrynowicz, Poznan University of Technology, Poznań, Poland
 +  * Weronika T. Adrian, AGH UST, Krakow, Poland
  
-===== Program Committee ===== 
  
-===== Important dates===== 
-  * ** Submission Deadline:** May 4, 2021 (AoE) 
-  * ** Notification of Acceptance:** May 25, 2021 (AoE) 
-  * ** Camera-Ready Versions Due:** June 6, 2021 (AoE) 
-  * ** Workshop date:** August 21-26, 2021 
  
 ===== Submission details ===== ===== Submission details =====
  
-Please submit papers using the dedicated [[https://easychair.org/conferences/?conf=sedami2021|Easychair]]  We are accepting short papers – 5 pages with references, and long papers – 10 pages. We are encouraging both original research papers, as well position papers. All submissions should be formatted using the [[https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines|Springer LNCS format]].  Workshop proceedings will be made available by CEUR-WS. post workshop journal publication is considered.+ 
 +{{:sedami:ccis-logo.jpg?200 |}}The publication of proceedings (full papers only) of the SEDAMI will  be part of the [[https://www.springer.com/series/7899|Springer's CCIS]] book series. It will be possible to make individual papers Open Access, at the discretion and cost of the authors, by following the Springer procedure described [[https://www.springer.com/gp/computer-science/lncs/open-access-publishing-in-computer-proceedings|here]]. 
 + 
 +Please submit papers using the dedicated [[https://easychair.org/conferences/?conf=sedami2023|Easychair]]  We are accepting short papers that will not be published in Springer CCIS book – 5-6 pages (not including references), and full papers – 10-15 pages (not including references). We are encouraging both original research papers, as well position papers. All submissions should be formatted using the [[https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines|Springer LNCS format]].   
 + 
 +Furthermore, we encourage tool presentations. Depending on the number of submissions, long papers will be 20-30 minutes and short papers 15-20 minutes including Q&A. For the workshop we are expecting around 20-30 participants to attend. 
 + 
 +All submitted papers must: 
 +  * be written in English; 
 +  * contain author names, affiliations, and email addresses; 
 +  * be formatted according to the [[https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines|Springer LNCS template]]; 
 +  * be in PDF (make sure that the PDF can be viewed on any platform). 
  
sedami/start.1617262400.txt.gz · Last modified: 2021/04/01 07:33 by sbk
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