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» A New Framework for Dissimilarity and Similarity Learning
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PAKDD
2010
ACM
130views Data Mining» more  PAKDD 2010»
13 years 9 months ago
A New Framework for Dissimilarity and Similarity Learning
Adam Woznica, Alexandros Kalousis
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
13 years 10 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
AAAI
2007
13 years 7 months ago
Semi-Supervised Learning by Mixed Label Propagation
Recent studies have shown that graph-based approaches are effective for semi-supervised learning. The key idea behind many graph-based approaches is to enforce the consistency bet...
Wei Tong, Rong Jin
CPM
2001
Springer
211views Combinatorics» more  CPM 2001»
13 years 9 months ago
Fuzzy Hamming Distance: A New Dissimilarity Measure
Lempel Ziv Coding (Extended Abstract). . . . . . . . . . . . . . . . . . . . . . . 18 Shmuel Tomi Klein, Yair Wiseman Approximate Matching of Run-Length Compressed Strings . . . . ...
Abraham Bookstein, Shmuel T. Klein, Timo Raita
WEBI
2005
Springer
13 years 10 months ago
A Novel Way of Computing Similarities between Nodes of a Graph, with Application to Collaborative Recommendation
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a M...
François Fouss, Alain Pirotte, Marco Saeren...