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AAAI
2006
14 years 11 months ago
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Yi Liu, Rong Jin, Liu Yang
80
Voted
ACL
2006
14 years 11 months ago
A FrameNet-Based Semantic Role Labeler for Swedish
We present a FrameNet-based semantic role labeling system for Swedish text. As training data for the system, we used an annotated corpus that we produced by transferring FrameNet ...
Richard Johansson, Pierre Nugues
77
Voted
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
15 years 10 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
14 years 11 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
75
Voted
NLE
2008
140views more  NLE 2008»
14 years 9 months ago
Active learning and logarithmic opinion pools for HPSG parse selection
For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
Jason Baldridge, Miles Osborne