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» A DOP Model for Semantic Interpretation
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APSEC
2007
IEEE
16 years 11 days ago
Towards Instant Automatic Model Refinement Based on OCL
Model refinement is a complex task. It is difficult for developers to refine models all by themselves. A good modeling tool should not only do routine refinement work for develope...
Hui Song, Yanchun Sun, Li Zhou, Gang Huang
ECTEL
2009
Springer
15 years 10 months ago
Getting to Know Your User - Unobtrusive User Model Maintenance within Work-Integrated Learning Environments
Work-integrated learning (WIL) poses unique challenges for user model design: on the one hand users’ knowledge levels need to be determined based on their work activities – tes...
Stefanie N. Lindstaedt, Günter Beham, Barbara...
TKDE
2010
224views more  TKDE 2010»
15 years 4 months ago
Probabilistic Topic Models for Learning Terminological Ontologies
—Probabilistic topic models were originally developed and utilised for document modeling and topic extraction in Information Retrieval. In this paper we describe a new approach f...
Wang Wei, Payam M. Barnaghi, Andrzej Bargiela
CIKM
2010
Springer
15 years 4 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
ISCI
2008
181views more  ISCI 2008»
15 years 6 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao