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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
SIGIR
2006
ACM
14 years 1 months ago
Probabilistic latent query analysis for combining multiple retrieval sources
Combining the output from multiple retrieval sources over the same document collection is of great importance to a number of retrieval tasks such as multimedia retrieval, web retr...
Rong Yan, Alexander G. Hauptmann
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
14 years 2 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
DILS
2005
Springer
14 years 1 months ago
Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources
Abstract. We present INDUS (Intelligent Data Understanding System), a federated, query-centric system for knowledge acquisition from autonomous, distributed, semantically heterogen...
Doina Caragea, Jyotishman Pathak, Jie Bao, Adrian ...
IJCAI
2007
13 years 9 months ago
Learning Semantic Descriptions of Web Information Sources
The Internet is full of information sources providing various types of data from weather forecasts to travel deals. These sources can be accessed via web-forms, Web Services or RS...
Mark James Carman, Craig A. Knoblock