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In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. During the expansion process, label propagation algorithm is used to select the most confident entity pairs and context patterns. The label propagation algorithm is a graph based semi-supervised learning method which models...
To understand text contents better, many research efforts have been made exploring detection and classification of the semantic relation between a concept pair. As described herein, we present our study of a semantic relation classification task as a graph-based multi-view learning task: each intra-view graph is constructed with instances in the view; a node's label ldquoscorerdquo is propagated on...
Traditional negative selection algorithms do not perform any differentiation for training self dataset and only use the mechanism of negative selection. They will generate excessive invalid detectors and have poor detection performance when the training selves contain noisy data. In this paper, an outlier robust algorithm is proposed. The new algorithm will divide the training selves into internal...
This paper proposes a pain expression recognition method using boosted Gabor features. At first, each neonatal facial image which is normalized to the size of 112times92 pixels is convoluted with the 2D Gabor filters to extract 412160 Gabor features. Since the high-dimensional Gabor feature vectors are quite redundant, we propose a modified version of AdaBoost algorithm, called the HybridBoost, to...
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