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» Meaningful Change Detection in Structured Data
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SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 4 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,...
BMCBI
2010
150views more  BMCBI 2010»
13 years 7 months ago
MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure
Background: The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of th...
Sriganesh Srihari, Kang Ning, Hon Wai Leong
ICDM
2005
IEEE
272views Data Mining» more  ICDM 2005»
14 years 1 months ago
Mining Patterns of Change in Remote Sensing Image Databases
Remote sensing image databases are the fastest growing archives of spatial information. However, we still have a limited capacity for extracting information from large remote sens...
Marcelino Pereira dos Santos Silva, Gilberto C&aci...
ACL
2000
13 years 9 months ago
Inducing Probabilistic Syllable Classes Using Multivariate Clustering
An approach to automatic detection of syllable structure is presented. We demonstrate a novel application of EM-based clustering to multivariate data, exempli ed by the induction ...
Karin Müller, Bernd Möbius, Detlef Presc...
CIKM
2011
Springer
12 years 7 months ago
Detecting anomalies in graphs with numeric labels
This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-rela...
Michael Davis, Weiru Liu, Paul Miller, George Redp...