1st Call For Papers

1st Workshop on Multi-Source Data Mining (MSDM 2020)
Co-located with ICDM 2020, Sorrento, Italy
November 17, 2020

Website: https://msdm20.loria.fr

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Important dates
Paper submission deadline: August 24, 2020
Notification of paper acceptance: September 17, 2020
Camera-ready version deadline: September 24, 2020
Workshop (at ICDM 2020): November 17, 2020

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Description & Objectives
The generalisation 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.

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Topics of interest
We welcome contributions of researchers and practitioners, including preliminary works and results and position papers, 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, user modelling, prediction and prescription, etc.

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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.

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Organizers
Armelle Brun - LORIA, Universite de Lorraine, France
Anne Boyer - LORIA, Universite de Lorraine, France

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