Please use this identifier to cite or link to this item:
https://olympias.lib.uoi.gr/jspui/handle/123456789/14413Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Exarchos, T. P. | en |
| dc.contributor.author | Tsipouras, M. G. | en |
| dc.contributor.author | Papaloukas, C. | en |
| dc.contributor.author | Fotiadis, D. I. | en |
| dc.date.accessioned | 2015-11-24T17:37:52Z | - |
| dc.date.available | 2015-11-24T17:37:52Z | - |
| dc.identifier.issn | 0169-023X | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/14413 | - |
| dc.rights | Default Licence | - |
| dc.subject | sequential pattern mining | en |
| dc.subject | sequential pattern matching | en |
| dc.subject | sequence classification | en |
| dc.subject | recognition | en |
| dc.subject | machines | en |
| dc.title | A two-stage methodology for sequence classification based on sequential pattern mining and optimization | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.identifier.primary | DOI 10.1016/j.datak.2008.05.007 | - |
| heal.identifier.secondary | <Go to ISI>://000258801400007 | - |
| heal.identifier.secondary | http://ac.els-cdn.com/S0169023X08000748/1-s2.0-S0169023X08000748-main.pdf?_tid=099a97a427b1514744cf1439ea293940&acdnat=1339756685_f74d41c7a3f56360c3cc2f1991b6018a | - |
| heal.language | en | - |
| heal.access | campus | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικών | el |
| heal.publicationDate | 2008 | - |
| heal.abstract | We present a methodology for sequence classification, which employs sequential pattern mining and optimization, in a two-stage process. In the first stage, a sequence classification model is defined, based on a set of sequential patterns and two sets of weights are introduced, one for the patterns and one for classes. In the second stage, an optimization technique is employed to estimate the weight values and achieve optimal classification accuracy. Extensive evaluation of the methodology is carried out, by varying the number of sequences, the number of patterns and the number of classes and it is compared with similar sequence classification approaches. (c) 2008 Elsevier B.V. All rights reserved. | en |
| heal.publisher | Elsevier | en |
| heal.journalName | Data & Knowledge Engineering | en |
| heal.journalType | peer reviewed | - |
| heal.fullTextAvailability | TRUE | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Exarchos-2008-A two-stage methodol.pdf | 514.48 kB | Adobe PDF | View/Open Request a copy |
This item is licensed under a Creative Commons License
