DocumentCode :
2710495
Title :
Discovering Significant Patterns in Multi-stream Sequences
Author :
Gwadera, Robert ; Crestani, Fabio
Author_Institution :
Fac. of Inf., Univ. of Lugano, Lugano
fYear :
2008
fDate :
15-19 Dec. 2008
Firstpage :
827
Lastpage :
832
Abstract :
Discovering significant patterns in synchronized multi-stream sequences also known as multi-attribute event sequences (multi-sequences), is an important problem in many domains, including monitoring systems and information retrieval. In this paper we propose a new approach for assessing significance of multi-stream patterns in multi-attribute event sequences. In experiments on physiological multi-stream data we show applicability of our method.
Keywords :
information retrieval; information retrieval; monitoring systems; multi-attribute event sequences; multi-stream sequences; Biomedical monitoring; Data mining; Informatics; Information retrieval; Joining processes; Patient monitoring; Sensor phenomena and characterization; Sensor systems and applications; Telecommunication traffic; Time factors; multi-stream data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on
Conference_Location :
Pisa
ISSN :
1550-4786
Print_ISBN :
978-0-7695-3502-9
Type :
conf
DOI :
10.1109/ICDM.2008.146
Filename :
4781186
Link To Document :
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