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» Mining Multiple Large Databases
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ICDE
2010
IEEE
750views Database» more  ICDE 2010»
14 years 2 months ago
Efficient and accurate discovery of patterns in sequence datasets
Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require effici...
Avrilia Floratou, Sandeep Tata, Jignesh M. Patel
BMCBI
2006
195views more  BMCBI 2006»
13 years 10 months ago
Hubs of knowledge: using the functional link structure in Biozon to mine for biologically significant entities
Background: Existing biological databases support a variety of queries such as keyword or definition search. However, they do not provide any measure of relevance for the instance...
Paul Shafer, Timothy Isganitis, Golan Yona
SSDBM
2010
IEEE
185views Database» more  SSDBM 2010»
13 years 8 months ago
DESSIN: Mining Dense Subgraph Patterns in a Single Graph
Currently, a large amount of data can be best represented as graphs, e.g., social networks, protein interaction networks, etc. The analysis of these networks is an urgent research ...
Shirong Li, Shijie Zhang, Jiong Yang
PAKDD
2010
ACM
178views Data Mining» more  PAKDD 2010»
14 years 2 months ago
SkyDist: Data Mining on Skyline Objects
The skyline operator is a well established database primitive which is traditionally applied in a way that only a single skyline is computed. In this paper we use multiple skylines...
Christian Böhm, Annahita Oswald, Claudia Plan...
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
14 years 3 months ago
CLUMP: A Scalable and Robust Framework for Structure Discovery
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
Kunal Punera, Joydeep Ghosh