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Collecting quality data for database mining

conference contribution
posted on 2001-01-01, 00:00 authored by C Zhang, Shichao Zhang
Data collecting is necessary to some organizations such as nuclear power plants and earthquake bureaus, which have very small databases. Traditional data collecting is to obtain necessary data from internal and external data-sources and join all data together to create a homogeneous huge database. Because collected data may be untrusty, it can disguise really useful patterns in data. In this paper, breaking away traditional data collecting mode that deals with internal and external data equally, we argue that the first step for utilizing external data is to identify quality data in data-sources for given mining tasks. Pre- and post-analysis techniques are thus advocated for generating quality data.

History

Title of proceedings

AI 2001 : Advances in Artificial Intelligence : Proceedings of the 14th Australian Joint Conference on Artificial Intelligence

Event

Australian Joint Conference on Artificial Intelligence (14th : 2001 : Adelaide)

Pagination

593 - 604

Publisher

Australian Joint Conference on Artificial Intelligence

Location

Adelaide, S.Aust.

Place of publication

[Adelaide, S.Aust.]

Start date

2001-12-10

End date

2001-12-14

ISBN-10

3540429603

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2001, Springer

Editor/Contributor(s)

M Stumptner, D Corbett, M Brooks

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