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SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
16 years 4 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
ICDE
2010
IEEE
263views Database» more  ICDE 2010»
16 years 4 months ago
Managing Uncertainty of XML Schema Matching
Abstract-- Despite of advances in machine learning technologies, a schema matching result between two database schemas (e.g., those derived from COMA++) is likely to be imprecise. ...
Reynold Cheng, Jian Gong, David W. Cheung
CCS
2009
ACM
15 years 11 months ago
Large-scale malware indexing using function-call graphs
A major challenge of the anti-virus (AV) industry is how to effectively process the huge influx of malware samples they receive every day. One possible solution to this problem i...
Xin Hu, Tzi-cker Chiueh, Kang G. Shin
DEXA
2009
Springer
151views Database» more  DEXA 2009»
15 years 11 months ago
Automatic Extraction of Ontologies Wrapping Relational Data Sources
Describing relational data sources (i.e. databases) by means of ontologies constitutes the foundation of most of the semantic based approaches to data access and integration. In sp...
Lina Lubyte, Sergio Tessaris
ACII
2007
Springer
15 years 10 months ago
Interpolating Expressions in Unit Selection
ended abstract reports on on-going work exploring the addition of a certain degree of control over expressivity in a unit selection context. Rather than merely choosing one unit se...
Marc Schröder