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Advances in Data Mining


Menge:  Stück  
Produktinformationen
cover
cover
Artikel-Nr.:
     5667A-9783540240549
Hersteller:
     Springer Verlag
Herst.-Nr.:
     9783540240549
EAN/GTIN:
     9783540240549
Suchbegriffe:
Bücher für Datenbanken - englischsp...
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The Industrial Conference on Data Mining ICDM-Leipzig was the fourth meeting in a series of annual events which started in 2000, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. The mission of the conference is to bring together researchers and people from industry in order to discuss together new trends and applications in data mining. This year a broad spectrum of work of different applications was presented ranging from image mining, medicine and biotechnology, management and environmental control, to telecommunications. Besides that an industrial exhibition showed the successful application of data mining methods by industries in different areas such as medical devices, mass data management systems, data mining tools, etc. During the discussion many projects were inspired leading to new and joint work. The fruitful discussions, the exchange of ideas and the spirit of the conference made it a remarkable event for both sides, industry and research. We would like to express our appreciation to the reviewers for their precise and highly professional work. We appreciate the help and understanding of the editorial staff at Springer and in particular Alfred Hofmann, who supported the publication of these proceedings in the LNAI series. Last, but not least, we wish to thank all speakers, participants and industrial exhibitors who contributed to the success of the conference. We are looking forward to welcoming you to ICDM 2005 (www.data-mini- forum.de) and to the new work you will present there.
Weitere Informationen:
Author:
Petra Perner
Verlag:
Springer Berlin
Sprache:
eng
Weitere Suchbegriffe: Data Mining (EDV), Case-Based Reasoning, access control, algorithmic learning, association rule mining, bioinformatics, business data mining, classification, clustering, data mining, image mining
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