Adaptive Anomaly Detection of Coupled Activity Sequences

DSpace/Manakin Repository

Search OPUS


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Ou, Y
dc.contributor.author Cao, L
dc.contributor.author Zhang, C
dc.date.accessioned 2010-05-28T09:47:12Z
dc.date.issued 2009-01
dc.identifier.citation The IEEE Intelligent Informatics Bulletin, 2009, 10 (1), pp. 12 - 16
dc.identifier.issn 1727-5997
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/9058
dc.description.abstract Many real-life applications often involve multiple sequences, which are coupled with each other. It is unreasonable to either study the multiple coupled sequences separately or simply merge them into one sequence, because the information about their interacting relationships would be lost. Furthermore, such coupled sequences also have frequently significant changes which are likely to degrade the performance of trained model. Taking the detection of abnormal trading activity patterns in stock markets as an example, this paper proposes a Hidden Markov Model-based approach to address the above two issues. Our approach is suitable for sequence analysis on multiple coupled sequences and can adapt to the significant sequence changes automatically. Substantial experiments conducted on a real dataset show that our approach is effective.
dc.publisher IEEE
dc.title Adaptive Anomaly Detection of Coupled Activity Sequences
dc.type Journal Article
dc.parent The IEEE Intelligent Informatics Bulletin
dc.journal.volume 1
dc.journal.volume 10
dc.journal.number 1 en_US
dc.publocation United States of America en_US
dc.identifier.startpage 12 en_US
dc.identifier.endpage 16 en_US
dc.cauo.name FEIT.A/DRsch Ctr Quantum Computat'n & Intelligent Systs en_US
dc.conference Verified OK en_US
dc.for 0807 Library and Information Studies
dc.for 0806 Information Systems
dc.personcode 011221
dc.personcode 034535
dc.personcode 999551
dc.percentage 50 en_US
dc.classification.name Information Systems en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Multiple coupled sequences, Anomaly, HMM, Adaptation, Stock market. en_US
dc.description.keywords Multiple coupled sequences, Anomaly, HMM, Adaptation, Stock market.
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


Files in this item

This item appears in the following Collection(s)

Show simple item record