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» Efficient Evaluation of XQuery over Streaming Data
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PVLDB
2008
116views more  PVLDB 2008»
13 years 8 months ago
Tighter estimation using bottom k sketches
Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a ...
Edith Cohen, Haim Kaplan
ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 6 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 11 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
SIGKDD
2008
125views more  SIGKDD 2008»
13 years 8 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun
TIP
2010
121views more  TIP 2010»
13 years 3 months ago
Optimal PET Protection for Streaming Scalably Compressed Video Streams With Limited Retransmission Based on Incomplete Feedback
For streaming scalably compressed video streams over unreliable networks, Limited-Retransmission Priority Encoding Transmission (LR-PET) outperforms PET remarkably since the opport...
Ruiqin Xiong, David Taubman, Vijay Sivaraman