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» Anomaly detection in data represented as graphs
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CCCG
2008
13 years 9 months ago
On the Complexity of Point Recolouring in Geometric Graphs
Given a collection of points representing geographic data we consider the task of delineating boundaries based on the features of the points. Assuming that the features are binary...
Henk Meijer, Yurai Núñez Rodrí...
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 8 months 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...
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 9 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 10 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
MICCAI
2009
Springer
13 years 9 months ago
Optimal Graph Search Segmentation Using Arc-weighted Graph for Simultaneous Surface Detection of Bladder and Prostate
We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic a...
Qi Song, Xiaodong Wu, Yunlong Liu, Mark Smith, Joh...