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» Multi-label Feature Selection for Graph Classification
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ICDE
2007
IEEE
182views Database» more  ICDE 2007»
14 years 6 months ago
Discriminative Frequent Pattern Analysis for Effective Classification
The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graph...
Hong Cheng, Xifeng Yan, Jiawei Han, Chih-Wei Hsu
ICIP
2009
IEEE
13 years 3 months ago
Selecting representative and distinctive descriptors for efficient landmark recognition
To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales a...
Sheng Gao, Joo-Hwee Lim
ACL
2006
13 years 6 months ago
Combining Association Measures for Collocation Extraction
We introduce the possibility of combining lexical association measures and present empirical results of several methods employed in automatic collocation extraction. First, we pre...
Pavel Pecina, Pavel Schlesinger
ICML
2003
IEEE
14 years 6 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
ICDM
2006
IEEE
166views Data Mining» more  ICDM 2006»
13 years 11 months ago
Mining Generalized Graph Patterns Based on User Examples
There has been a lot of recent interest in mining patterns from graphs. Often, the exact structure of the patterns of interest is not known. This happens, for example, when molecu...
Pavel Dmitriev, Carl Lagoze