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» Report from the first Workshop on Extremely Large Databases
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KDD
2006
ACM
142views Data Mining» more  KDD 2006»
14 years 7 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
ESE
2006
199views Database» more  ESE 2006»
13 years 7 months ago
Experiences from introducing UML-based development in a large safety-critical project
UML and UML-based development methods have become de facto standards in industry, and there are many claims for the positive effects of modelling object-oriented systems using meth...
Bente Anda, Kai Hansen, Ingolf Gullesen, Hanne Kri...
PR
2008
117views more  PR 2008»
13 years 7 months ago
A scale-free distribution of false positives for a large class of audio similarity measures
The "bag-of-frames" approach (BOF) to audio pattern recognition models signals as the long-term statistical distribution of their local spectral features, a prototypical...
Jean-Julien Aucouturier, François Pachet
KDD
2004
ACM
285views Data Mining» more  KDD 2004»
14 years 24 days ago
Effective localized regression for damage detection in large complex mechanical structures
In this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. Every mechanical structure is defi...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
MM
1994
ACM
143views Multimedia» more  MM 1994»
13 years 11 months ago
Quad-Tree Segmentation for Texture-Based Image Query
In this paper we propose a technique for segmenting images by texture content with application to indexing images in a large image database. Using a quad-tree decomposition, textu...
Jonathan M. Smith, Shih-Fu Chang