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AMW
2010
13 years 10 months ago
Robust Clustering of Data Streams using Incremental Optimization
Discovering the patterns in evolving data streams is a very important and challenging task. In many applications, it is useful to detect the dierent patterns evolving over time and...
Basheer Hawwash, Olfa Nasraoui
KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 9 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
EDBT
2006
ACM
150views Database» more  EDBT 2006»
14 years 9 months ago
On Futuristic Query Processing in Data Streams
Recent advances in hardware technology have resulted in the ability to collect and process large amounts of data. In many cases, the collection of the data is a continuous process ...
Charu C. Aggarwal
VLDB
2004
ACM
97views Database» more  VLDB 2004»
14 years 2 months ago
Progressive Optimization in Action
Progressive Optimization (POP) is a technique to make query plans robust, and minimize need for DBA intervention, by repeatedly re-optimizing a query during runtime if the cardina...
Vijayshankar Raman, Volker Markl, David E. Simmen,...
VLDB
1998
ACM
127views Database» more  VLDB 1998»
14 years 29 days ago
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...
Yasuhiko Morimoto, Takeshi Fukuda, Hirofumi Matsuz...