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VLDB
2005
ACM
141views Database» more  VLDB 2005»
15 years 5 months ago
Automatic Data Fusion with HumMer
Heterogeneous and dirty data is abundant. It is stored under different, often opaque schemata, it represents identical real-world objects multiple times, causing duplicates, and ...
Alexander Bilke, Jens Bleiholder, Christoph Bö...
VLDB
2005
ACM
140views Database» more  VLDB 2005»
15 years 5 months ago
Loadstar: Load Shedding in Data Stream Mining
In this demo, we show that intelligent load shedding is essential in achieving optimum results in mining data streams under various resource constraints. The Loadstar system intro...
Yun Chi, Haixun Wang, Philip S. Yu
VLDB
2005
ACM
196views Database» more  VLDB 2005»
15 years 5 months ago
Summarizing and Mining Inverse Distributions on Data Streams via Dynamic Inverse Sampling
Emerging data stream management systems approach the challenge of massive data distributions which arrive at high speeds while there is only small storage by summarizing and minin...
Graham Cormode, S. Muthukrishnan, Irina Rozenbaum
VLDB
2005
ACM
180views Database» more  VLDB 2005»
15 years 5 months ago
Cache-conscious Frequent Pattern Mining on a Modern Processor
In this paper, we examine the performance of frequent pattern mining algorithms on a modern processor. A detailed performance study reveals that even the best frequent pattern min...
Amol Ghoting, Gregory Buehrer, Srinivasan Parthasa...
VLDB
2005
ACM
177views Database» more  VLDB 2005»
15 years 5 months ago
Discovering Large Dense Subgraphs in Massive Graphs
We present a new algorithm for finding large, dense subgraphs in massive graphs. Our algorithm is based on a recursive application of fingerprinting via shingles, and is extreme...
David Gibson, Ravi Kumar, Andrew Tomkins