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» Learning from Multiple Sources of Inaccurate Data
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IJCAI
2003
13 years 8 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...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 8 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
KDD
2002
ACM
96views Data Mining» more  KDD 2002»
14 years 7 months ago
A theoretical framework for learning from a pool of disparate data sources
Shai Ben-David, Johannes Gehrke, Reba Schuller
SDM
2012
SIAM
307views Data Mining» more  SDM 2012»
11 years 10 months ago
Pseudo Cold Start Link Prediction with Multiple Sources in Social Networks
Link prediction is an important task in social networks and data mining for understanding the mechanisms by which the social networks form and evolve. In most link prediction rese...
Liang Ge, Aidong Zhang
IV
2010
IEEE
140views Visualization» more  IV 2010»
13 years 6 months ago
GVIS: An Integrating Infrastructure for Adaptively Mashing up User Data from Different Sources
In this article we present an infrastructure for creating mash up visual representations of the user profile that combines data from different sources. We explored this approach ...
Luca Mazzola, Riccardo Mazza