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PPOPP
2010
ACM
16 years 3 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 11 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 11 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 9 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 11 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...