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» Learning from Multiple Sources of Inaccurate Data
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ML
2000
ACM
124views Machine Learning» more  ML 2000»
15 years 6 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
CIKM
1995
Springer
15 years 10 months ago
Research Problems in Data Warehousing
The topic of data warehousing encompasses architectures, algorithms, and tools for bringing together selected data from multiple databases or other information sources into a sing...
Jennifer Widom
HICSS
2003
IEEE
174views Biometrics» more  HICSS 2003»
15 years 11 months ago
Semantic Interoperability in the Fixed Income Securities Industry: A Knowledge Representation Architecture for Dynamic Integrati
We examine a knowledge representation architecture to support context interchange mediation. For autonomous receivers and sources sharing a common subject domain, the mediator’s...
Allen Moulton, Stuart E. Madnick, Michael Siegel
AAAI
2006
15 years 7 months ago
Efficient Active Fusion for Decision-Making via VOI Approximation
Active fusion is a process that purposively selects the most informative information from multiple sources as well as combines these information for achieving a reliable result ef...
Wenhui Liao, Qiang Ji
DOLAP
2008
ACM
15 years 8 months ago
Data mining-based fragmentation of XML data warehouses
With the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data warehouses fail...
Hadj Mahboubi, Jérôme Darmont