1st Workshop on Multi-Source Data Mining

(MSDM'20)

Held in conjunction with the 20th IEEE International Conference on Data Mining (ICDM 2020)
17-20 November 2020

About the workshop

The generalization of digital technology has generated a huge amount of data, collected from various sources, and that can be spread out in different places.

Mining multiple sources of data to discover useful information is of critical importance for decision making. Indeed, these data sources can represent several dimensions or points of view about a phenomenon. However, how to efficiently mine quality information from multiple data sources is still a challenging task for current research, as in real world applications, data stored in multiple places by different, owned by different stakeholder, often conflict: data name, format, value or point of view may be different. Furthermore, data can be heterogeneous in their structure, sequential or not, …

The main objective of the1st International Workshop on Multi-Source Data Mining (MSDM)  is to discuss promising and recent research, applicative problems and results behind current multi data source mining.

We invite you to participate in the 1st  edition of the International Workshop on Multi-Source Data Mining (MSDM), to be held during the IEEE International Conference on Data Mining – ICDM (http://icdm2020.bigke.org/), 2020 in Sorrento, Italy.

The workshop’s aim is to contribute to bringing together approaches defined or used, when data sources are multiple, possibly heterogeneous, represent multiple points of view, are possibly linked, even through time, including from the applicative point of view.

Topics of interest

We welcome contributions of researchers and practitioners that address (but are not limited to) the following topics of interest: 

  • Algorithms and models for multi-source data mining
  • Multi-relational data mining
  • Heterogeneous data mining (including graph, structured/semi-structured data, text, spatio-temporal, time-series, streaming data) 
  • Multi-dimensional data mining
  • Redescription mining
  • Temporal multi-source mining
  • Big data mining
  • Practical applications of multi source data mining, including recommender systems.

Preliminary works and results are welcome, as well as position papers.

Submissions

Authors are encouraged to send their contribution of max 8 pages plus 2 extra pages in the IEEE 2-column format, including the bibliography and any possible appendices.

Submissions longer than 10 pages will be rejected without review. All submissions will be peer reviewed by the Workshop Program Committee on the basis of technical quality, relevance to scope of the workshop, originality, significance, and clarity. 

For paper submission, please proceed to the submission website.

Important dates

August 24, 2020: Workshop papers submission
September 17, 2020: Notification of workshop papers acceptance to authors
September 24, 2020: Camera-ready deadline and copyright form
November 17, 2020: Workshop date

Organizers

Dr. Armelle Brun, LORIA – Université de Lorraine, France
Pr. Anne Boyer, LORIA – Université de Lorraine, France

Program committee

Dr. Armelle Brun, LORIA – Université de Lorraine, France
Pr. Anne Boyer, LORIA – Université de Lorraine, France
Agathe Merceron, Beuth University of Applied Sciences, Berlin, Germany
Aysegul Yildiz Ulus, University of Galatasaray, Turkey
Cyril De Runz, LIFAT, Université de Tours, France
Esther Galbrun, School of Computing, University of Eastern Finland, Finland
Frédéric Blanchard, Université de Reims Champagne-Ardennes, France
Nicolas Lachiche, Université de Strasbourg, France
Sandra Bringay, LIRMM, Université de Montpellier, France
Shengrui Wang, Université de Sherbrooke, Canada
Yannick Toussaint, LORIA, Université de Lorraine, France

Contact information

Please send enquiries to brun at loria dot fr

Thème : Overlay par Kaira.