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» Learning Overcomplete Representations
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112
Voted
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
15 years 2 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
104
Voted
COLING
2000
15 years 2 months ago
Learning Semantic-Level Information Extraction Rules by Type-Oriented ILP
This paper describes an approach to using semantic rcprcsentations for learning information extraction (IE) rules by a type-oriented inductire logic programming (ILl)) system. NLP...
Yutaka Sasaki, Yoshihiro Matsuo
109
Voted
STAIRS
2008
109views Education» more  STAIRS 2008»
15 years 2 months ago
Representing Case Variations for Learning General and Specific Adaptation Rules
Adaptation is a task of case-based reasoning systems that is largely domain-dependant. This motivates the study of adaptation knowledge acquisition (AKA) that can be carried out th...
Fadi Badra, Jean Lieber
69
Voted
AAAI
2006
15 years 2 months ago
Learning Noun-Modifier Semantic Relations with Corpus-based and WordNet-based Features
We study the performance of two representations of word meaning in learning noun-modifier semantic relations. One representation is based on lexical resources, in particular WordN...
Vivi Nastase, Jelber Sayyad-Shirabad, Marina Sokol...
96
Voted
ECML
1998
Springer
15 years 5 months ago
First-Order Learning for Web Mining
We present compelling evidence that the World Wide Web is a domain in which applications can benefit from using first-order learning methods, since the graph structure inherent in ...
Mark Craven, Seán Slattery, Kamal Nigam