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» Efficient Discovery of Confounders in Large Data Sets
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RIVF
2008
13 years 10 months ago
Simple but effective methods for combining kernels in computational biology
Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
GEOINFORMATICA
2007
223views more  GEOINFORMATICA 2007»
13 years 8 months ago
Algorithms for Nearest Neighbor Search on Moving Object Trajectories
Nearest Neighbor (NN) search has been in the core of spatial and spatiotemporal database research during the last decade. The literature on NN query processing algorithms so far d...
Elias Frentzos, Kostas Gratsias, Nikos Pelekis, Ya...
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 6 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 9 months ago
De-duping URLs via rewrite rules
A large fraction of the URLs on the web contain duplicate (or near-duplicate) content. De-duping URLs is an extremely important problem for search engines, since all the principal...
Anirban Dasgupta, Ravi Kumar, Amit Sasturkar
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 9 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal