Introduction to algorithms
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recognition of emergent human behaviour in a smart home: A data mining approach
Pervasive and Mobile Computing
A daily behavior enabled hidden Markov model for human behavior understanding
Pattern Recognition
An adaptive anomaly detector for worm detection
SYSML'07 Proceedings of the 2nd USENIX workshop on Tackling computer systems problems with machine learning techniques
Extracting spatiotemporal human activity patterns in assisted living using a home sensor network
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Abnormal behavior detection for early warning of terrorist attack
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
IEEE Transactions on Image Processing
Abnormal behaviours identification for an elder's life activities using dissimilarity measurements
Proceedings of the 4th International Conference on PErvasive Technologies Related to Assistive Environments
A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living
Expert Systems with Applications: An International Journal
Design of a situation-aware system for abnormal activity detection of elderly people
AMT'12 Proceedings of the 8th international conference on Active Media Technology
A survey of intrusion detection techniques for cyber-physical systems
ACM Computing Surveys (CSUR)
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In recent years, there is a growing interest about assisted living environments especially for the elderly who live alone, due to the increasing number of aged people. In order for them to live safe and healthy, we need to detect abnormal behavior that may cause severe and emergent situations for the elderly. In this work, we suggest a method that detects abnormal behavior using wireless sensor networks. We model an episode that is a series of events, which includes spatial and temporal information about the subject being monitored. We define a similarity scoring function that compares two episodes taking into consideration temporal aspects. We propose a way to determine a threshold to divide episodes into two groups that reduces wrong classification. Weights on individual functions that consist the similarity function are determined experimentally so that they can produce the good results in terms of area under curve in receiver operating characteristic (ROC) curve.