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ICPR
2004
IEEE
16 years 3 months ago
A Probabilistic Approach to Learning Costs for Graph Edit Distance
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
Horst Bunke, Michel Neuhaus
ICCBR
2003
Springer
15 years 7 months ago
Using Evolution Programs to Learn Local Similarity Measures
Abstract. The definition of similarity measures is one of the most crucial aspects when developing case-based applications. In particular, when employing similarity measures that ...
Armin Stahl, Thomas Gabel
CICLING
2006
Springer
15 years 5 months ago
Application of Semi-supervised Learning to Evaluative Expression Classification
Abstract. We propose to use semi-supervised learning methods to classify evaluative expressions, that is, tuples of subjects, their attributes, and evaluative words, that indicate ...
Yasuhiro Suzuki, Hiroya Takamura, Manabu Okumura
FLAIRS
2008
15 years 4 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
TRECVID
2008
15 years 3 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...