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» CURE: An Efficient Clustering Algorithm for Large Databases
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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 9 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
KDD
2004
ACM
114views Data Mining» more  KDD 2004»
16 years 3 months ago
Scalable mining of large disk-based graph databases
Mining frequent structural patterns from graph databases is an interesting problem with broad applications. Most of the previous studies focus on pruning unfruitful search subspac...
Chen Wang, Wei Wang 0009, Jian Pei, Yongtai Zhu, B...
232
Voted
ICDE
2004
IEEE
116views Database» more  ICDE 2004»
16 years 4 months ago
An Efficient Algorithm for Mining Frequent Sequences by a New Strategy without Support Counting
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
Ding-Ying Chiu, Yi-Hung Wu, Arbee L. P. Chen
166
Voted
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
16 years 3 months ago
IncSpan: incremental mining of sequential patterns in large database
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Hong Cheng, Xifeng Yan, Jiawei Han
133
Voted
IDEAL
2004
Springer
15 years 9 months ago
PRICES: An Efficient Algorithm for Mining Association Rules
In this paper, we present PRICES, an efficient algorithm for mining association rules, which first identifies all large itemsets and then generates association rules. Our approach ...
Chuan Wang, Christos Tjortjis