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CORR
2007
Springer
170views Education» more  CORR 2007»
15 years 6 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...
JFR
2006
75views more  JFR 2006»
15 years 6 months ago
Topological map learning from outdoor image sequences
We propose an approach to building topological maps of environments based on image sequences. The central idea is to use manifold constraints to find representative feature protot...
Xuming He, Richard S. Zemel, Volodymyr Mnih
ACL
2010
15 years 4 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
RECSYS
2010
ACM
15 years 4 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
ACL
2009
15 years 4 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov