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Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases
TLDR
In this survey we provide an overview of the current state of the art in querying multimedia databases, describing the index structures and algorithms for an efficient query processing in high-dimensional spaces. Expand
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Density connected clustering with local subspace preferences
TLDR
In this paper, we introduce the concept of local subspace preferences, which captures the main directions of high point density. Expand
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A cost model for nearest neighbor search in high-dimensional data space
TLDR
We present a new cost model for nearest neighbor search in high-dimensional data space which takes boundary effects into account and is applicable to different data distributions and index structures. Expand
  • 406
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Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease
TLDR
We developed a novel data mining framework in combination with three different classifiers including support vector machine (SVM), Bayes statistics, and voting feature intervals (VFI) to derive a quantitative index of pattern matching for the prediction of the conversion from MCI to AD. Expand
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Independent quantization: an index compression technique for high-dimensional data spaces
TLDR
In this paper, we present the IQ-tree, a new index compression technique for high-dimensional data spaces that combines the advantages of hierarchical search and a fast linear search. Expand
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The k-Nearest Neighbour Join: Turbo Charging the KDD Process
  • C. Böhm, F. Krebs
  • Mathematics, Computer Science
  • Knowledge and Information Systems
  • 1 November 2004
TLDR
We propose a new algorithm to compute the k-nearest neighbour join using the multipage index (MuX), a specialised index structure for the similarity join. Expand
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Epsilon grid order: an algorithm for the similarity join on massive high-dimensional data
TLDR
We propose the Epsilon Grid Order, a new algorithm for determining the similarity join of very large data sets, which is based on a particular sort order of the data points. Expand
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Computing Clusters of Correlation Connected objects
TLDR
In this paper, we propose a method called 4C (Computing Correlation Connected Clusters) to identify local subgroups of the data objects sharing a uniform but arbitrarily complex correlation. Expand
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Improving the Query Performance of High-Dimensional Index Structures by Bulk-Load Operations
TLDR
In this paper, we propose a new bulk-loading technique for high-dimensional indexes which represent an important component of multimedia database systems. Expand
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Density-based clustering using graphics processors
TLDR
In this paper, we propose CUDA-DClust, a massively parallel algorithm for density-based clustering for the use of a Graphics Processing Unit (GPU). Expand
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