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KDD
2012
ACM
271views Data Mining» more  KDD 2012»
13 years 8 months ago
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...
ICCV
2003
IEEE
16 years 8 months ago
Tracking Objects Using Density Matching and Shape Priors
We present a novel method for tracking objects by combining density matching with shape priors. Density matching is a tracking method which operates by maximizing the Bhattacharyy...
Tao Zhang, Daniel Freedman
ICPR
2006
IEEE
16 years 7 months ago
Part-Based Probabilistic Point Matching
Correspondence algorithms typically struggle with shapes that display part-based variation. We present a probabilistic approach that matches shapes using independent part transfor...
Graham McNeill, Sethu Vijayakumar
SEMWEB
2009
Springer
16 years 29 days ago
Scalable Matching of Industry Models - a Case Study
A recent approach to the problem of ontology matching has been to convert the problem of ontology matching to information retrieval. We explore the utility of this approach in matc...
Brian Byrne, Achille Fokoue, Aditya Kalyanpur, Kav...
AAAI
1998
15 years 7 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge