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DIS
2007
Springer
15 years 11 months ago
Efficient Incremental Mining of Top-K Frequent Closed Itemsets
In this work we study the mining of top-K frequent closed itemsets, a recently proposed variant of the classical problem of mining frequent closed itemsets where the support thresh...
Andrea Pietracaprina, Fabio Vandin
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
16 years 7 months ago
Using and Learning Semantics in Frequent Subgraph Mining
The search for frequent subgraphs is becoming increasingly important in many application areas including Web mining and bioinformatics. Any use of graph structures in mining, howev...
Bettina Berendt
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
16 years 4 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
ICDM
2007
IEEE
121views Data Mining» more  ICDM 2007»
16 years 1 months ago
ORIGAMI: Mining Representative Orthogonal Graph Patterns
In this paper, we introduce the concept of α-orthogonal patterns to mine a representative set of graph patterns. Intuitively, two graph patterns are α-orthogonal if their simila...
Mohammad Al Hasan, Vineet Chaoji, Saeed Salem, J&e...
CIKM
2006
Springer
15 years 10 months ago
TRIPS and TIDES: new algorithms for tree mining
Recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. In this paper, we address the problem of...
Shirish Tatikonda, Srinivasan Parthasarathy, Tahsi...