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ECML
2001
Springer
13 years 11 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
IRAL
2003
ACM
14 years 7 days ago
Korean named entity recognition using HMM and CoTraining model
Namedentityrecognition isimportantinsophisticatedinformation service system such as Question Answering and Text Mining since most of the answer type and text mining unit depend on...
Euisok Chung, Yi-Gyu Hwang, Myung-Gil Jang
COLING
2008
13 years 8 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
CVPR
2008
IEEE
13 years 7 months ago
Joint learning and dictionary construction for pattern recognition
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
Duc-Son Pham, Svetha Venkatesh
EMNLP
2007
13 years 8 months ago
Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors
One may need to build a statistical parser for a new language, using only a very small labeled treebank together with raw text. We argue that bootstrapping a parser is most promis...
David A. Smith, Jason Eisner