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» On Mining Closed Sets in Multi-Relational Data
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ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
14 years 2 months ago
Finding Maximal Fully-Correlated Itemsets in Large Databases
—Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. Much previous research focuses on finding ...
Lian Duan, William Nick Street
BMCBI
2004
173views more  BMCBI 2004»
13 years 7 months ago
d-matrix - database exploration, visualization and analysis
Background: Motivated by a biomedical database set up by our group, we aimed to develop a generic database front-end with embedded knowledge discovery and analysis features. A maj...
Dominik Seelow, Raffaello Galli, Siegrun Mebus, Ha...
PAMI
2010
164views more  PAMI 2010»
13 years 6 months ago
Large-Scale Discovery of Spatially Related Images
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Ondrej Chum, Jiri Matas
CIARP
2009
Springer
13 years 11 months ago
A Brief Index for Proximity Searching
A large number of computer tasks can be modeled as the search for an object near a given query. From multimedia databases to learning algorithms, data mining and pattern recognitio...
Eric Sadit Tellez, Edgar Chávez, Antonio Ca...
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...