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HIPC
2003
Springer
16 years 2 days ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
194
Voted
BMCBI
2005
108views more  BMCBI 2005»
15 years 6 months ago
Storing, linking, and mining microarray databases using SRS
Background: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range ...
Antoine Veldhoven, Don de Lange, Marcel Smid, Vict...
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
154
Voted
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...