The Industrial Conference on Data Mining ICDM is held on yearly basis .Researcher and Industrial People from different fields will present theoretical aspects and their applications, and the results obtained by applying data mining. Besides that, newcomers in the field can get a fast introduction to Data Mining by taking the tutorial running in connection with the conference. In a special industry session practitioners from different industrial branches can present their ongoing projects and discuss their work with the auditorium. An industrial exhibition, where companies present their data-mining tools, will round up the conference. Four workshops are running in connection with the conference: Data Mining in Life Sciences DMLS, Case-Based Reasoning CBR-MD, Data Mining in Marketing, and Workshop Data Mining in Agriculture. Other proposals for workshops are welcome and can be submitted to info@data-mining-forum.de.In a problem/solution hour you will have the opportunity to present your application and ask for support by researchers. The social events will give you the opportunity to meet top leading researchers in Data Mining and Machine Learning from all over the world. We encourage industrial people to show their applications and projects in data mining. This work can be presented as poster during the poster session in the special Industry Track. Please submit a one page abstract including title, name and affiliation.Accepted industry presentation will be published in the Series Industry Proceedings "Advances in Data Mining". The size of the paper can range form 1 up to 5 pages in Springer LNCS format.

Workshops 

• International Workshop on Data Mining in Marketing, DMM 2024
•  International Workshop Case-Based Reasoning, CBR-MD 2024
•  International Workshop of Advanced Internet of Things for Medicine and Others - IoTMO 2024
•  The Internet of Things and Services International Workshop on Multimedia Forensic Data Analysis, Forensic 2024

   Read on: data-mining-forum.de

Continue reading at data-mining-forum.de

Data Analytics Insight & Analysis

Facebook Share

Twitter Share

Linkedin Share

Email Share