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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10016/10606
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| Title: | Sequence classification using statistical pattern recognition |
| Author(s): | Iglesias, José Antonio
Ledezma, Agapito
Sanchis, Araceli |
| Publisher: | Springer |
| Issued date: | 2007 |
| 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 |
| URI: | http://hdl.handle.net/10016/10606 |
| ISBN: | 978-3-540-74824-3 |
| ISSN: | 0302-9743 (print)
1611-3349 (online) |
| DOI: | http://dx.doi.org/10.1007/978-3-540-74825-0_19 |
| Description: | Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Slovenia, September, 6th-8th, 2007. |
| 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. |
| Sponsor: | This work has been supported by the Spanish Government under project TRA2004-07441-C03-2/IA. |
| Serie / Nº.: | Lecture notes in computer science, 2007, Vol. 4723 |
| Publisher version: | http://dx.doi.org/10.1007/978-3-540-74825-0_19 |
| Keywords: | Sequence Classification
Sequence Learning
Statistical Pattern Recognition
Behavior Recognition |
| Rights: | © Springer-Verlag Berlin Heidelberg |
| Appears in Collections: | DI - CAOS - Capítulos de Monografías
DI - CAOS - Comunicaciones en Congresos y otros eventos
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