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» Discovering Classification from Data of Multiple Sources
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KDD
2009
ACM
204views Data Mining» more  KDD 2009»
14 years 8 months ago
Improving classification accuracy using automatically extracted training data
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...
COMAD
2008
13 years 9 months ago
Information Integration Across Heterogeneous Sources: Where Do We Stand and How to Proceed?
Today, information integration has assumed a completely different, complex connotation than what it used to be. The advent of the Internet, the proliferation of information source...
Aditya Telang, Sharma Chakravarthy, Yan Huang
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
14 years 1 months ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
DILS
2006
Springer
13 years 11 months ago
A Method for Similarity-Based Grouping of Biological Data
Similarity-based grouping of data entries in one or more data sources is a task underlying many different data management tasks, such as, structuring search results, removal of red...
Vaida Jakoniene, David Rundqvist, Patrick Lambrix
3DOR
2009
13 years 8 months ago
A 3D Shape Benchmark for Retrieval and Automatic Classification of Architectural Data
When drafting new buildings, architects make intensive use of existing 3D models including building elements, furnishing, and environment elements. These models are either directl...
Raoul Wessel, Ina Blümel, Reinhard Klein