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» Fusing Approximate Knowledge from Distributed Sources
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ISVC
2009
Springer
13 years 12 months ago
Biometric Recognition: When Is Evidence Fusion Advantageous?
Abstract. Having assessed the performance gains due to evidence fusion, previous works reported contradictory conclusions. For some, a consistent improvement is achieved, while oth...
Hugo Proença
IJCAI
2003
13 years 6 months ago
Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources
With the growing use of distributed information networks, there is an increasing need for algorithmic and system solutions for data-driven knowledge acquisition using distributed,...
Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vas...
DATAMINE
2006
130views more  DATAMINE 2006»
13 years 5 months ago
Mining Adaptive Ratio Rules from Distributed Data Sources
Different from traditional association-rule mining, a new paradigm called Ratio Rule (RR) was proposed recently. Ratio rules are aimed at capturing the quantitative association kno...
Jun Yan, Ning Liu, Qiang Yang, Benyu Zhang, QianSh...
AAAI
2010
13 years 5 months ago
Inducing Probability Distributions from Knowledge Bases with (In)dependence Relations
When merging belief sets from different agents, the result is normally a consistent belief set in which the inconsistency between the original sources is not represented. As proba...
Jianbing Ma, Weiru Liu, Anthony Hunter
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
13 years 12 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon