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ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
15 years 8 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
106
Voted
ICDS
2010
IEEE
15 years 7 months ago
Towards Learning Domain Ontology from Legacy Documents
—Learning ontology from text is a challenge in knowledge engineering research and practice. Learning relations between concepts is even more difficult work. However, when conside...
Yijian Wu, Shaolei Zhang, Wenyun Zhao
78
Voted
IADIS
2004
15 years 3 months ago
Modes of Delivery and Learning Objectives
The purpose of the study was to determine public university South Dakota (USA) distance faculty perceptions regarding intended level of learning objectives for four selected modes...
Jack Fei Yang
DIGITEL
2007
IEEE
15 years 8 months ago
MuDiS - A Virtual Learning Environment
This paper presents a multi-component; distributed system (MuDiS) based solution for building a virtual learning environment which combines a wide range of technology, tools and d...
Jeetinder Singh, Jayanthi Sivaswamy, Krishnarajulu...
119
Voted
CIKM
2005
Springer
15 years 7 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia