Iglesias Martínez, José AntonioLedezma Espino, Agapito IsmaelSanchis de Miguel, María Araceli2011-04-052011-04-052007Advances in Intelligent Data Analysis VII: 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007. Springer, 2007, pp. 207-218978-3-540-74824-30302-9743 (print)1611-3349 (online)https://hdl.handle.net/10016/10606Proceeding of: 7th International Symposium on Intelligent Data Analysis. IDA-2007. Ljubljana, Slovenia, September, 6th-8th, 2007.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.text/plainapplication/pdfeng© Springer-Verlag Berlin HeidelbergSequence ClassificationSequence LearningStatistical Pattern RecognitionBehavior Recognitionconference paperInformática10.1007/978-3-540-74825-0_19open access207218Advances in Intelligent Data Analysis VII: 7th International Symposium on Intelligent Data Analysis, IDA 2007