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KDD
2005
ACM
178views Data Mining» more  KDD 2005»
15 years 11 months ago
Failure detection and localization in component based systems by online tracking
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
Haifeng Chen, Guofei Jiang, Cristian Ungureanu, Ke...
KDD
2009
ACM
193views Data Mining» more  KDD 2009»
16 years 9 days ago
Category detection using hierarchical mean shift
Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to iden...
Pavan Vatturi, Weng-Keen Wong
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 6 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 6 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
16 years 9 days ago
Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...
Lei Shi, Vandana Pursnani Janeja