Data broadcasting is well known for its excellent scalability. Multi-dimensional range queries, such as spatial range queries of geographical information for location dependent se...
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...