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» Learning consumer preferences using semantic similarity
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CVPR
2008
IEEE
14 years 11 months ago
Semi-supervised boosting using visual similarity learning
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Christian Leistner, Helmut Grabner, Horst Bischof
IEAAIE
2010
Springer
13 years 7 months ago
Learning User Preferences to Maximise Occupant Comfort in Office Buildings
It is desirable to ensure that the thermal comfort conditions in offices are in line with the preferences of occupants. Controlling their offices correctly therefore requires the c...
Anika Schumann, Nic Wilson, Mateo Burillo
JODS
2006
206views Data Mining» more  JODS 2006»
13 years 9 months ago
Emergent Semantics in Knowledge Sifter: An Evolutionary Search Agent Based on Semantic Web Services
This paper addresses the various facets of emergent semantics in content retrieval systems such as Knowledge Sifter, an architecture and system based on the use of specialized agen...
Larry Kerschberg, Hanjo Jeong, Wooju Kim
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
14 years 10 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
ACL
2009
13 years 7 months ago
Do Automatic Annotation Techniques Have Any Impact on Supervised Complex Question Answering?
In this paper, we analyze the impact of different automatic annotation methods on the performance of supervised approaches to the complex question answering problem (defined in th...
Yllias Chali, Sadid A. Hasan, Shafiq R. Joty