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» Mining Supplemental Frequent Patterns
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KDD
2008
ACM
192views Data Mining» more  KDD 2008»
14 years 10 months ago
Partial least squares regression for graph mining
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Hiroto Saigo, Koji Tsuda, Nicole Krämer
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
14 years 10 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
SIGMOD
2004
ACM
162views Database» more  SIGMOD 2004»
14 years 10 months ago
Graph Indexing: A Frequent Structure-based Approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is...
Xifeng Yan, Philip S. Yu, Jiawei Han
ISCI
2008
116views more  ISCI 2008»
13 years 10 months ago
Discovery of maximum length frequent itemsets
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often ...
Tianming Hu, Sam Yuan Sung, Hui Xiong, Qian Fu
DMIN
2006
137views Data Mining» more  DMIN 2006»
13 years 11 months ago
Discovering of Frequent Itemsets with CP-mine Algorithm
Efficient algorithms to discover frequent patterns are crucial in data mining research. Several effective data structures, such as two-dimensional arrays, graphs, trees, and tries ...
Nuansri Denwattana, Yutthana Treewai