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» Mining for Structural Anomalies in Graph-based Data
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CIKM
2011
Springer
12 years 4 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...
PAKDD
2010
ACM
171views Data Mining» more  PAKDD 2010»
13 years 3 months ago
Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach
With the rapid development of information technology, many applications have to deal with potentially infinite data streams. In such a dynamic context, storing the whole data stre...
Yoann Pitarch, Anne Laurent, Pascal Poncelet
VLDB
2007
ACM
179views Database» more  VLDB 2007»
14 years 5 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 2 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,...
CIDM
2009
IEEE
13 years 11 months ago
Mining for insider threats in business transactions and processes
—Protecting and securing sensitive information are critical challenges for businesses. Deliberate and intended actions such as malicious exploitation, theft or destruction of dat...
William Eberle, Lawrence B. Holder