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CIB
2004
57views more  CIB 2004»
13 years 7 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
CEC
2008
IEEE
14 years 2 months ago
Distributed multi-relational data mining based on genetic algorithm
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
Wenxiang Dou, Jinglu Hu, Kotaro Hirasawa, Gengfeng...
TKDE
1998
111views more  TKDE 1998»
13 years 7 months ago
Efficient Data Mining for Path Traversal Patterns
—In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects...
Ming-Syan Chen, Jong Soo Park, Philip S. Yu
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 5 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
KDD
2005
ACM
170views Data Mining» more  KDD 2005»
14 years 8 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua