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Data Mining and Modeling in Scientific Databases.

Epaminondas Kapetanios, Moira C. Norrie: Data Mining and Modeling in Scientific Databases. SSDBM 1997: 24-27
@inproceedings{DBLP:conf/ssdbm/KapetaniosN97,
  author    = {Epaminondas Kapetanios and
               Moira C. Norrie},
  editor    = {Yannis E. Ioannidis and
               David M. Hansen},
  title     = {Data Mining and Modeling in Scientific Databases},
  booktitle = {Ninth International Conference on Scientific and Statistical
               Database Management, Proceedings, August 11-13, 1997, Olympia,
               Washington, USA},
  publisher = {IEEE Computer Society},
  year      = {1997},
  isbn      = {0-8186-7952-2},
  pages     = {24-27},
  ee        = {db/conf/ssdbm/KapetaniosN97.html},
  crossref  = {DBLP:conf/ssdbm/97},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

In the last decades, the execution of various scientific experiments aiming at a more comprehensive understanding of our environment, has shown a tremendous increase in data production. Database models provide a more or less adequate mechanism for mapping real-world applications into a computer-bound reality. Since scientific knowledge can be modelled a-priori only to some extent, the question which arises here is how able is a database schema to evolve. On the other side, knowledge can be provided by the underlying scientific data on which data mining algorithms are applied. The main question which arises here is how to provide a suitable environment in order to accomodate the results coming out from data analysis tasks and how these tasks can be supported by a database model.

Copyright © 1997 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.

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Yannis E. Ioannidis, David M. Hansen (Eds.): Ninth International Conference on Scientific and Statistical Database Management, Proceedings, August 11-13, 1997, Olympia, Washington, USA. IEEE Computer Society 1997, ISBN 0-8186-7952-2
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