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BMCBI
2011
12 years 10 months ago
MINE: Module Identification in NEtworks
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
Kahn Rhrissorrakrai, Kristin C. Gunsalus
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
14 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
IDA
2007
Springer
13 years 6 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
CGF
2010
189views more  CGF 2010»
13 years 6 months ago
Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
ICDE
2007
IEEE
99views Database» more  ICDE 2007»
14 years 8 months ago
Source-aware Entity Matching: A Compositional Approach
Entity matching (a.k.a. record linkage) plays a crucial role in integrating multiple data sources, and numerous matching solutions have been developed. However, the solutions have...
Warren Shen, Pedro DeRose, Long Vu, AnHai Doan, Ra...