Publication: Sequence classification using statistical pattern recognition
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ISSN: 0302-9743 (print)
ISSN: 1611-3349 (online)
ISBN: 978-3-540-74824-3
Publication date
2007
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Springer
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Abstract
Sequence classification is a significant problem that arises in many different real-world applications. The purpose of a sequence classifier is to assign a class label to a given sequence. Also, to obtain the pattern that characterizes the sequence is usually very useful. In this paper, a technique to discover a pattern from a given sequence is presented followed by a general novel method to classify the sequence. This method considers mainly the dependencies among the neighbouring elements of a sequence. In order to evaluate this method, a UNIX command environment is presented, but the method is general enough to be applied to other environments.
Description
Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Slovenia, September, 6th-8th, 2007.
Keywords
Sequence Classification, Sequence Learning, Statistical Pattern Recognition, Behavior Recognition
Bibliographic citation
Advances in Intelligent Data Analysis VII: 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007. Springer, 2007, pp. 207-218