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KDD
2000
ACM
81views Data Mining» more  KDD 2000»
15 years 10 months ago
Targeting the right students using data mining
The education domain offers a fertile ground for many interesting and challenging data mining applications. These applications can help both educators and students, and improve th...
Yiming Ma, Bing Liu, Ching Kian Wong, Philip S. Yu...
DAGSTUHL
2007
15 years 8 months ago
Model-Driven Development for End-Users, too!?
iary models in order to bridge the semantic gap between high-level, abstract user requirements and low-level, concrete programs and to support a stepwise refinement process. This d...
Gregor Engels
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 8 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...
TRECVID
2008
15 years 8 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
DAGSTUHL
2006
15 years 8 months ago
The Space of Cognitive Vision
Cognitive vision is an area that is not yet well-defined, in the sense that one can unambiguously state what issues fall under its purview and what considerations do not. Neither i...
David Vernon