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» Learning Relations Using Collocations
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CEAS
2006
Springer
14 years 1 months ago
Learning at Low False Positive Rates
Most spam filters are configured for use at a very low falsepositive rate. Typically, the filters are trained with techniques that optimize accuracy or entropy, rather than perfor...
Wen-tau Yih, Joshua Goodman, Geoff Hulten
DAGM
2008
Springer
13 years 12 months ago
Learning Visual Compound Models from Parallel Image-Text Datasets
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...
WWW
2008
ACM
14 years 11 months ago
Using the wisdom of the crowds for keyword generation
In the sponsored search model, search engines are paid by businesses that are interested in displaying ads for their site alongside the search results. Businesses bid for keywords...
Ariel Fuxman, Panayiotis Tsaparas, Kannan Achan, R...
COLING
2008
13 years 11 months ago
ILP-based Conceptual Analysis for Chinese NPs
In this paper, we explore a conceptual resource for Chinese nominal phrases, which allows multi-dependency and distinction between dependency and the corresponding exact relation....
Paul D. Ji, Stephen G. Pulman
ICML
2004
IEEE
14 years 11 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...