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SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
15 years 9 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
16 years 13 days ago
SNARE: a link analytic system for graph labeling and risk detection
Classifying nodes in networks is a task with a wide range of applications. It can be particularly useful in anomaly and fraud detection. Many resources are invested in the task of...
Mary McGlohon, Stephen Bay, Markus G. Anderle, Dav...
KDD
2004
ACM
143views Data Mining» more  KDD 2004»
16 years 8 days ago
Incremental maintenance of quotient cube for median
Data cube pre-computation is an important concept for supporting OLAP(Online Analytical Processing) and has been studied extensively. It is often not feasible to compute a complet...
Cuiping Li, Gao Cong, Anthony K. H. Tung, Shan Wan...
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 8 days 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
164views Data Mining» more  KDD 2009»
16 years 13 days ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang