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FQAS
2004
Springer
146views Database» more  FQAS 2004»
13 years 11 months ago
Discovering Representative Models in Large Time Series Databases
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Simona E. Rombo, Giorgio Terracina
BMCBI
2008
129views more  BMCBI 2008»
13 years 8 months ago
Mining phenotypes for gene function prediction
Background: Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In ...
Philip Groth, Bertram Weiss, Hans-Dieter Pohlenz, ...
AUSAI
2003
Springer
14 years 1 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
14 years 1 months ago
Pruning Social Networks Using Structural Properties and Descriptive Attributes
Scale is often an issue with understanding and making sense of large social networks. Here we investigate methods for pruning social networks by determining the most relevant rela...
Lisa Singh, Lise Getoor, Louis Licamele
SSDBM
2010
IEEE
185views Database» more  SSDBM 2010»
13 years 6 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