The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
: Monte Carlo Study of Taxonomy Evaluation Alexander Ulanov, Georgy Shevlyakov, Nikolay Lyubomishchenko, Pankaj Mehra, Vladimir Polutin HP Laboratories HPL-2010-147 Taxonomy evalu...
Alexander Ulanov, Georgy Shevlyakov, Nikolay Lyubo...
Two trends are converging to make the CPU cost of a table scan a more important component of database performance. First, table scans are becoming a larger fraction of the query p...
Allison L. Holloway, Vijayshankar Raman, Garret Sw...
The important challenge of evaluating XPath queries over XML streams has sparked much interest in the past few years. A number of algorithms have been proposed, supporting wider f...
One possible threat to linked data quality is the lack of knowledge about the dynamics in dependent remote datasets. Linked data consuming applications often need to be aware of ch...
Niko Popitsch, Bernhard Haslhofer, Elaheh Momeni R...