Management of uncertainty in database systems
Modern database systems
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
On the Surprising Behavior of Distance Metrics in High Dimensional Spaces
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Anomaly Detection over Noisy Data using Learned Probability Distributions
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
ADMIT: anomaly-based data mining for intrusions
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Issues in data stream management
ACM SIGMOD Record
Aurora: a data stream management system
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Streaming pattern discovery in multiple time-series
VLDB '05 Proceedings of the 31st international conference on Very large data bases
An Empirical Bayes Approach to Detect Anomalies in Dynamic Multidimensional Arrays
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
The 8 requirements of real-time stream processing
ACM SIGMOD Record
Research issues in data stream association rule mining
ACM SIGMOD Record
Outlier detection by active learning
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Automatic outlier detection for time series: an application to sensor data
Knowledge and Information Systems - Special Issue on Mining Low-Quality Data
Malicious Node Detection in Wireless Sensor Networks Using an Autoregression Technique
ICNS '07 Proceedings of the Third International Conference on Networking and Services
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A Cost-Based Approach to Adaptive Resource Management in Data Stream Systems
IEEE Transactions on Knowledge and Data Engineering
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Borealis-R: a replication-transparent stream processing system for wide-area monitoring applications
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
SStreaMWare: a service oriented middleware for heterogeneous sensor data management
Proceedings of the 5th international conference on Pervasive services
Detecting Current Outliers: Continuous Outlier Detection over Time-Series Data Streams
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
The hitchhiker's guide to successful wireless sensor network deployments
Proceedings of the 6th ACM conference on Embedded network sensor systems
A Kalman Filter Based Approach for Outlier Detection in Sensor Networks
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 04
Semantics and implementation of continuous sliding window queries over data streams
ACM Transactions on Database Systems (TODS)
Flexible and scalable storage management for data-intensive stream processing
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Incremental outlier detection in data streams using local correlation integral
Proceedings of the 2009 ACM symposium on Applied Computing
ACM Computing Surveys (CSUR)
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Toward Simulation-Based Optimization in Data Stream Management Systems
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Detection of unique temporal segments by information theoretic meta-clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
ORDEN: outlier region detection and exploration in sensor networks
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
WSFI-Mine: Mining Frequent Patterns in Data Streams
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
An online spatio-temporal association rule mining framework for analyzing and estimating sensor data
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Distance-based outlier queries in data streams: the novel task and algorithms
Data Mining and Knowledge Discovery
Research issues in mining multiple data streams
Proceedings of the First International Workshop on Novel Data Stream Pattern Mining Techniques
DBOD-DS: distance based outlier detection for data
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Online outlier detection for data streams
Proceedings of the 15th Symposium on International Database Engineering & Applications
Towards a secure data stream management system
TEAA'05 Proceedings of the 31st VLDB conference on Trends in Enterprise Application Architecture
AnyOut: anytime outlier detection on streaming data
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Change Detection in Streaming Multivariate Data Using Likelihood Detectors
IEEE Transactions on Knowledge and Data Engineering
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In applications, such as sensor networks and power usage monitoring, data are in the form of streams, each of which is an infinite sequence of data points with explicit or implicit timestamps and has special characteristics, such as transiency, uncertainty, dynamic data distribution, multidimensionality, and dynamic relationship. These characteristics introduce new research issues that make outlier detection for stream data more challenging than that for regular (non-stream) data. This paper discusses those research issues for applications where data come from a single stream as well as multiple streams.