Neural Method for Detection of Complex Patterns in Databases

Authors:
Chao Deng;Fanlun Xiong
Affiliations:
-;-
Venue:
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Year:
1999

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Abstract

Databases storing real data contain complex patterns, such as chaotic pattern which generally are characteristics of greatly random fluctuation that often appear between deterministic and stochastic patterns of knowledge discovery in database. Chaotic patterns are always treated as random fluctuation distributions and ignored in literature so far. A novel network approach to discover and predict chaotic pattern in databases is proposed in this paper, which together with Zytkow's Forty-Niner can not only discover the chaotic pattern but also predict it efficiently. In addition, this approach is very suitable to deal with large databases and has extensive applicable prospects in the vivid research fields of KDD.