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FSKD
2005
Springer
267views Fuzzy Logic» more  FSKD 2005»
14 years 3 months ago
Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
Discovery of interesting or frequently appearing time series patterns is one of the important tasks in various time series data mining applications. However, recent research critic...
Tak-Chung Fu, Fu-Lai Chung, Robert W. P. Luk, Chak...
ENC
2004
IEEE
14 years 1 months ago
Efficient Data Structures and Parallel Algorithms for Association Rules Discovery
Discovering patterns or frequent episodes in transactions is an important problem in data-mining for the purpose of infering deductive rules from them. Because of the huge size of...
Christophe Cérin, Gay Gay, Gaël Le Mah...
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 11 months ago
An Algorithm for the Discovery of Arbitrary Length Ordinal Association Rules
Association rule mining techniques are used to search attribute-value pairs that occur frequently together in a data set. Ordinal association rules are a particular type of associa...
Alina Campan, Gabriela Serban, Traian Marius Truta...
SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
13 years 11 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
DAWAK
2010
Springer
13 years 10 months ago
Discovery and Application of Functional Dependencies in Conjunctive Query Mining
Abstract. We present an algorithm for mining frequent queries in arbitrary relational databases, over which functional dependencies are assumed. Building upon previous results, we ...
Bart Goethals, Dominique Laurent, Wim Le Page