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PPOPP
2010
ACM
15 years 9 months ago
A distributed placement service for graph-structured and tree-structured data
Effective data placement strategies can enhance the performance of data-intensive applications implemented on high end computing clusters. Such strategies can have a significant i...
Gregory Buehrer, Srinivasan Parthasarathy, Shirish...
CLOUD
2010
ACM
15 years 4 months ago
Comet: batched stream processing for data intensive distributed computing
Batched stream processing is a new distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired...
Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, B...
DOLAP
2004
ACM
15 years 5 months ago
Handling big dimensions in distributed data warehouses using the DWS technique
The DWS (Data Warehouse Striping) technique allows the distribution of large data warehouses through a cluster of computers. The data partitioning approach partition the facts tab...
Marco Costa, Henrique Madeira
CIKM
2006
Springer
15 years 3 months ago
Incremental hierarchical clustering of text documents
Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, ...
Nachiketa Sahoo, Jamie Callan, Ramayya Krishnan, G...
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 5 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...