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sedami:start [2021/08/20 15:05] – [Schedule] 2papers gjnsedami:start [2022/06/24 10:36] – [Submission details] sbk
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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/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://2022.ecmlpkdd.org/|European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022)]].
 +
 +The [[start2021|1st edition of SEDAMI]] was co-located with [[https://ijcai-21.org/|30th International Joint Conference on Artificial Intelligence (IJCAI-21)]]
 +
 +
 +====== SEDAMI 2022 at ECML PKDD 2022 ======
  
 **Organising committee** **Organising committee**
  
-  * Martin Atzmueller,  Osnabrück University, Germany, 
   * Grzegorz J. Nalepa,  Jagiellonian University, Poland   * Grzegorz J. Nalepa,  Jagiellonian University, Poland
 +  * Martin Atzmueller,  Osnabrück University & German Research Center for AI (DFKI), Germany,
   * Szymon Bobek,  Jagiellonian University   * Szymon Bobek,  Jagiellonian University
   * Nada Lavrac, Jožef Stefan Institute, Slovenia   * Nada Lavrac, Jožef Stefan Institute, Slovenia
-====== SEDAMI 2021 at IJCAI 2021 ====== 
  
 ===== Important dates===== ===== Important dates=====
-  * ** Submission Deadline:** May 13, 2021 (AoE)+  * ** Submission Deadline:** June 12, 2022 (AoE)
   * //We plan to have a rolling review process for late/breaking papers of 5-6 pp. This will be kept open for up to 1 months after the regular deadlines//   * //We plan to have a rolling review process for late/breaking papers of 5-6 pp. This will be kept open for up to 1 months after the regular deadlines//
-  * ** Notification of Acceptance:** May 25, 2021 (AoE) +  * ** Notification of Acceptance:** July 11, 2022 (AoE) 
-  * ** Camera-Ready Versions Due:** June 6, 2021 (AoE) +  * ** Camera-Ready Versions Due:** July 25, 2022 (AoE) 
-  * ** Workshop date:** August 21-26, 2021+  * ** Workshop date:** September 19, 2022
  
-===== Schedule =====+===== Call for papers =====
  
-**Aug 20 10:00 – 13:30 Montreal Time (UTC-4)** +{{ :sedami:sedami2022-cfp1.pdf |Call For Papers -- SEDAMI 2022}}
- +
-Please note, that all times are in UTC-4 (this is e.g., CEST-6 ... 10:00 UTC-4 is 16:00 CEST) +
- +
-**10:00-10:15** SEDAMI 2021 - Opening (Chair: Martin Atzmueller) +
- +
-**10:15-11:45** Session 1 - Foundations (Chair: Szymon Bobek)\\ +
-10:15-10:45 Victor Guimarães and Vítor Costa: {{:sedami:sedami2021-victorguimaraes.pdf|Meta-Interpretive Learning meets Neural Networks}}\\ +
-10:45-11:15 Blaž Škrlj and Nada Lavrač: {{:sedami:sedami2021-blazskrlj.pdf|Towards Explainable Relational Boosting via Propositionalization}}\\ +
-11:15-11:45 Dietmar Seipel and Martin Atzmueller: {{:sedami:sedami2021-dietmarseipel.pdf|Declarative Knowledge Discovery in Databases via Meta-Learning - Towards Advanced Analytics}} +
- +
-**11:45-12:00** Break +
- +
-**12:00-13:00** Session 2 - Modeling & Application (Chair: Nada Lavrac)\\ +
-12:00-12:30 Shaobo Wang, Guangliang Liu, Wenyan Zhu, Zengtao Jiao, Haichen Lv, Jun Yan and Yunlong Xia: {{:sedami:sedami2021-shaobowang.pdf|Interpretable Knowledge Mining for Heart Failure Prognosis Risk Evaluation}}\\ +
-12:30-13:00 Dan Hudson, Leonid Schwenke, Stefan Bloemheuvel, Arnab Ghosh Chowdhury, Nils Schut and Martin Atzmueller: {{ :sedami:sedami2021-danhudson.pdf|Knowledge-Augmented Induction of Complex Networks on Supply-Demand-Material Data +
-}} +
- +
-**13:00-13:30** Closing (Chair: Grzegorz J. Nalepa) +
- +
-===== Call for papers =====+
  
-{{ :sedami:sedami2021-cfp.pdf |Call For Papers -- SEDAMI 2021}} +===== Aims and Scope =====
-===== Motivation for the workshop =====+
 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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 topics which include but are not limited to: topics which include but are not limited to:
  
-  * Declarative data mining +    * Workshop topics include (but are not limited to): 
-  * Declarative domain knowledge +    * Introduction of semantics into the data mining process 
-  * Knowledge modelling and data mining +    * Declarative domain knowledge 
-  * Data mining and machine learning using ontologies +    * Declarative data mining 
-  * Introduction of semantics into the data mining process +    * Knowledge modelling and data mining 
-  * Interpretable models in data mining and machine learning +    * Feature engineering for transparency and explanation 
-  * Knowledge-based data mining and machine learning approaches +    * Knowledge-based data mining approaches 
-  * Role of explanations in data mining and machine learning +    * Knowledge-graphs in data mining 
-  * Knowledge-graphs in data mining and machine learning +    * Interpretable models in data mining 
-  * Feature engineering for transparency and explanation +    * Role of explanations in data mining 
-  * Transparent and hybrid models in machine learning +    * Inductive logic programming and data mining 
-  * Inductive logic programming and data mining +    * Transparent and hybrid models in data mining 
-  * Human in the loop of the data mining process +    * Human in the loop of the data mining process 
-  * Role of Linked Open Data in data mining +    * Role of Linked Open Data in data mining 
-  * Applications of all of the above +    * Applications of all of the above
- +
  
  
 ===== Program Committee (tentative) ===== ===== Program Committee (tentative) =====
  
-  * Klaus-Dieter Althoff, University of Hildesheim & DFKI, Germany +TBA
-  * Martin Atzmueller, Osnabrück University, Germany +
-  * Przemysław Biecek, Warsaw University of Technology, Poland +
-  * Szymon Bobek, Jagiellonian University, Poland +
-  * João Gama, University of Porto, Portugal   +
-  * Nada Lavrac, Jožef Stefan Institute, Slovenia +
-  * Stan Matwin, Dalhousie University, Canada +
-  * Grzegorz J. Nalepa, Jagiellonian University, Poland +
-  * Sławomir Nowaczyk, Halmstad University, Sweden +
-  * Jose Palma, Universidad de Murcia, Spain +
-  * Juan Pavon, Universidad Complutense de Madrid, Spain +
-  * Marc Plantevit, Université Lyon, France +
-  * Eric Postma, Tilburg University, The Netherlands +
-  * Céline Rouveirol, Université Sorbonne Paris Nord, France +
-  * Marek Sikora, Silesian University of Technology, Poland +
-  * Blaž Škrlj, Jožef Stefan Institute, Slovenia +
- +
  
  
 ===== Submission details ===== ===== Submission details =====
  
-Please submit papers using the dedicated [[https://easychair.org/conferences/?conf=sedami2021|Easychair]]  We are accepting short papers – 5-6 pages with references, and long papers – 10-12 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. A post workshop journal publication is considered. +Please submit papers using the dedicated [[https://easychair.org/conferences/?conf=sedami2022|Easychair]]   
- +We are accepting short papers – 5-6 pages with references, and long papers – 10-12 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.+The papers need to be prepared in CEUR-WS format (see below). 
 +Papers are to be submitted via Easychair. 
 +Workshop post-proceedings will be made available via CEUR-WS.  
 +A post workshop journal publication is considered.
  
-All submitted papers must:+All submitted papers must
   * be written in English;   * be written in English;
   * contain author names, affiliations, and email addresses;   * 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 formatted according to the CEUR-WS template http://ceur-ws.org/Vol-XXX/CEURART.zip (Overleaf version of the template: https://www.overleaf.com/read/gwhxnqcghhdt)
   * be in PDF (make sure that the PDF can be viewed on any platform).   * be in PDF (make sure that the PDF can be viewed on any platform).
  
sedami/start.txt · Last modified: 2023/09/29 06:57 by sbk
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