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CVIU
2011
12 years 11 months ago
Graph attribute embedding via Riemannian submersion learning
In this paper, we tackle the problem of embedding a set of relational structures into a metric space for purposes of matching and categorisation. To this end, we view the problem ...
Haifeng Zhao, Antonio Robles-Kelly, Jun Zhou, Jian...
WWW
2007
ACM
14 years 8 months ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva
ACL
2010
13 years 5 months ago
Hierarchical Sequential Learning for Extracting Opinions and Their Attributes
Automatic opinion recognition involves a number of related tasks, such as identifying the boundaries of opinion expression, determining their polarity, and determining their inten...
Yejin Choi, Claire Cardie
CVPR
2007
IEEE
14 years 9 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
IEEEICCI
2005
IEEE
14 years 1 months ago
Formal concept analysis based on hierarchical class analysis
The study of concept formation and learning is a central topic in cognitive informatics. Formal concept analysis can be viewed as an approach on this topic based on a formal conte...
Yaohua Chen, Yiyu Yao