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» Discovering Classification from Data of Multiple Sources
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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
BMCBI
2010
195views more  BMCBI 2010»
13 years 2 months ago
MBAT: A scalable informatics system for unifying digital atlasing workflows
Background: Digital atlases provide a common semantic and spatial coordinate system that can be leveraged to compare, contrast, and correlate data from disparate sources. As the q...
Daren Lee, Seth Ruffins, Queenie Ng, Nikhil Sane, ...
BICOB
2010
Springer
13 years 5 months ago
Multiple Kernel Learning for Fold Recognition
Fold recognition is a key problem in computational biology that involves classifying protein sharing structural similarities into classes commonly known as "folds". Rece...
Huzefa Rangwala
ICPR
2010
IEEE
13 years 5 months ago
Data Classification on Multiple Manifolds
Unlike most previous manifold-based data classification algorithms assume that all the data points are on a single manifold, we expect that data from different classes may reside ...
Rui Xiao, Qijun Zhao, David Zhang, Pengfei Shi
AAAI
1996
13 years 8 months ago
Learning Models for Multi-Source Integration
One issue involved in accessing multiple heterogeneous information sources is how to integrate the retrieved data. SIMS, an information mediator, handles this problem by mapping t...
Sheila Tejada, Craig A. Knoblock, Steven Minton