Pattern discovery in probabilistic databases

Zhang, Shichao and Zhang, Chengqi 2001, Pattern discovery in probabilistic databases, in AI 2001 : Advances in Artificial Intelligence : Proceedings of the 14th Australian Joint Conference on Artificial Intelligence, [The Conference], [Adelaide, S.Aust.], pp. 619-630, doi: 10.1007/3-540-45656-2_53.

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Title Pattern discovery in probabilistic databases
Author(s) Zhang, Shichao
Zhang, Chengqi
Conference name Australian Joint Conference on Artificial Intelligence (14th : 2001 : Adelaide)
Conference location Adelaide, S.Aust.
Conference dates 10-14 Dec. 2001
Title of proceedings AI 2001 : Advances in Artificial Intelligence : Proceedings of the 14th Australian Joint Conference on Artificial Intelligence
Editor(s) Stumptner, Markus
Corbett, Dan
Brooks, Mike
Publication date 2001
Start page 619
End page 630
Publisher [The Conference]
Place of publication [Adelaide, S.Aust.]
Summary Modeling probabilistic data is one of important issues in databases due to the fact that data is often uncertainty in real-world applications. So, it is necessary to identify potentially useful patterns in probabilistic databases. Because probabilistic data in 1NF relations is redundant, previous mining techniques don’t work well on probabilistic databases. For this reason, this paper proposes a new model for mining probabilistic databases. A partition is thus developed for preprocessing probabilistic data in a probabilistic databases. We evaluated the proposed technique, and the experimental results demonstrate that our approach is effective and efficient.
ISBN 03540429603
Language eng
DOI 10.1007/3-540-45656-2_53
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2001, Springer
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