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» Structural Discovery of E-lessons
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182
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KDD
2012
ACM
242views Data Mining» more  KDD 2012»
13 years 7 months ago
Query-driven discovery of semantically similar substructures in heterogeneous networks
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
Xiao Yu, Yizhou Sun, Peixiang Zhao, Jiawei Han
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 5 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
146
Voted
SIGMOD
2004
ACM
184views Database» more  SIGMOD 2004»
16 years 4 months ago
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies
The rich dependency structure found in the columns of real-world relational databases can be exploited to great advantage, but can also cause query optimizers--which usually assum...
Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul B...
147
Voted
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
15 years 11 months ago
Knowledge Discovery from Citation Networks
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Y...
182
Voted
WSDM
2012
ACM
207views Data Mining» more  WSDM 2012»
14 years 3 days ago
Sequence clustering and labeling for unsupervised query intent discovery
One popular form of semantic search observed in several modern search engines is to recognize query patterns that trigger instant answers or domain-specific search, producing sem...
Jackie Chi Kit Cheung, Xiao Li