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CIKM
2008
Springer
13 years 11 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
WEBNET
2000
13 years 10 months ago
New Approaches to Law Education: Making the Case for Web-based Learning
: Web-based instruction and online learning are changing customary practices in education. As conventional patterns for content delivery are influenced by new and improving technol...
Jennifer Gramling, Tom Galligan, Jean A. Derco
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 7 months ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
PROMISE
2010
13 years 3 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 9 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...