Data mining and modeling in scientific databases

In the last few decades, the execution of various scientific experiments aimed at a more comprehensive understanding of one's 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 com...

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Bibliographic Details
Published inProceedings. Ninth International Conference on Scientific and Statistical Database Management (Cat. No.97TB100150) pp. 24 - 27
Main Authors Kapetanios, E., Norrie, M.C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1997
Subjects
Data analysis
Data mining
Humans
Logic
Neural networks
Pattern recognition
Statistical analysis
Statistics
Uncertainty
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Summary:In the last few decades, the execution of various scientific experiments aimed at a more comprehensive understanding of one's 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 arises of how able a database schema is to evolve. On the other hand, knowledge can be provided by the underlying scientific data on which data mining algorithms are applied. The main question which arises is how to provide a suitable environment in order to accommodate the results coming out from data analysis tasks and how these tasks can be supported by a database model.
ISBN:9780818679520
0818679522
DOI:10.1109/SSDM.1997.621146