Title
Mining Top-n Local Outliers in Constrained Spatial Networks
Abstract
Outlier mining, also called outlier detection, is a challenging research issue in data mining with important applications as intrusion detection, fraud detection and medical analysis. From the perspective of data, previous work on outlier mining have involved in various types of data such as spatial data, time series data, trajectory data, and sensor data. However, few of them have considered a constrained spatial networks data in which each object must reside or move along a certain edge. In fact, in such special constrained spatial network data environments, previous outlier definitions and the according mining algorithms could work neither properly nor efficiently. In this paper we introduce a new definition of density-based local outlier in constrained spatial networks that considers for each object the outlier-ness with respect to its k nearest neighbors. Moreover , to detect outliers efficiently, we propose a fast cluster-and-bound algorithm that first cluster on each individual edge, then estimate the outlying degree of each cluster and prune those that could not contain top-n outliers, therefore constraining the computation of outliers to only very limited objects. Experiments on synthetic data sets demonstrate the scalability, effectiveness and efficiency of our methods.
Year
DOI
Venue
2008
10.1007/978-3-540-88192-6_77
ADMA
Keywords
Field
DocType
data mining,spatial networks data,mining top-n local outliers,constrained spatial networks,spatial data,outlier mining,spatial network data environment,synthetic data set,density-based local outlier,time series data,sensor data,trajectory data,outlier detection,synthetic data,intrusion detection,k nearest neighbor
Spatial analysis,Anomaly detection,Data mining,Computer science,Data type,Artificial intelligence,Intrusion detection system,k-nearest neighbors algorithm,Spatial network,Pattern recognition,Outlier,Machine learning,Scalability
Conference
Volume
ISSN
Citations 
5139
0302-9743
0
PageRank 
References 
Authors
0.34
14
4
Name
Order
Citations
PageRank
Chongsheng Zhang1164.05
Zhongbo Wu244.14
Bo Qu300.34
Hong Chen49923.20