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Cited by 404

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Finding surprising patterns in a time series database in linear time and space

Keogh, Eamonn, Lonardi, Stefano, Chiu, Bill 'Yuan-chi'·2002·Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining

Abstract

The problem of finding a specified pattern in a time series database (i.e. query by content) has received much attention and is now a relatively mature field. In contrast, the important problem of enumerating all surprising or interesting patterns has received far less attention. This problem requires a meaningful definition of "surprise", and an efficient search technique. All previous attempts at finding surprising patterns in time series use a very limited notion of surprise, and/or do not scale to massive datasets. To overcome these limitations we introduce a novel technique that defines a pattern surprising if the frequency of its occurrence differs substantially from that expected by chance, given some previously seen data.

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Crossref · 10.1145/775047.775128

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Metadata

Authors
Keogh, E., Lonardi, S., & Chiu, B. '.-C.
Venue
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Publisher
ACM
Published
2002-07-23
Pages
550-556
OpenAlex
W1995003166
Cited by
404
References
1
FWCI
17.93
Type
conference paper
Language
en
Open access
closed

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