Collecting quality data for database mining


Autoria(s): Zhang, Chengqi; Zhang, Shichao
Contribuinte(s)

Stumptner, Markus

Corbett, Dan

Brooks, Mike

Data(s)

01/01/2001

Resumo

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. <br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30004556

Idioma(s)

eng

Publicador

Australian Joint Conference on Artificial Intelligence

Relação

http://dro.deakin.edu.au/eserv/DU:30004556/zhang-collectingquality-2001.pdf

http://dx.doi.org/10.1007/3-540-45656-2_51

Direitos

2001, Springer

Tipo

Conference Paper