A feature selection application using particle swarm optimization for learning concept detection
| dc.contributor.author | Korhan Günel | |
| dc.contributor.author | Kazım Erdoǧdu | |
| dc.contributor.author | Refet Polat | |
| dc.contributor.author | Yasin Ozarslan | |
| dc.contributor.editor | H. Adeli , A.M. Correia , S. Costanzo , L.P. Reis , A. Rocha | |
| dc.date.accessioned | 2025-10-06T17:52:01Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | Recent developments of computational intelligence on educational technology yield concept map mining as a new research area. Concept map mining covers the extraction of learning concepts specifying relations among them and generating a concept map from educational contents. In this study we focused on determining the features that characterize a learning concept extracted from an educational text as raw data. The first three features are detected by using a hybrid system of Multi Layer Perceptron (MLP) and Particle Swarm Optimization (PSO) and the performance of the applied method is gauged in the viewpoint of a typical classification problem. © 2017 Elsevier B.V. All rights reserved. | |
| dc.identifier.doi | 10.1007/978-3-319-56538-5_94 | |
| dc.identifier.isbn | 9783319604855, 9783319276427, 9783319419343, 9783319232034, 9783319938844, 9783642330414, 9783319262833, 9788132220084, 9783642375019, 9783030026820 | |
| dc.identifier.issn | 21945357, 21945365 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018597356&doi=10.1007%2F978-3-319-56538-5_94&partnerID=40&md5=8d7ae68cac7e1248d3c7a969cdc078ac | |
| dc.identifier.uri | https://gcris.yasar.edu.tr/handle/123456789/9732 | |
| dc.language.iso | English | |
| dc.publisher | Springer Verlag service@springer.de | |
| dc.relation.ispartof | 5th World Conference on Information Systems and Technologies WorldCIST | |
| dc.source | Advances in Intelligent Systems and Computing | |
| dc.subject | Artificial Intelligence On Educational Technology, Concept Map Mining, Feature Selection, Particle Swarm Optimization, Pso, Swarm Intelligence, Artificial Intelligence, Education, Educational Technology, Feature Extraction, Hybrid Systems, Information Systems, Swarm Intelligence, Concept Detection, Concept Maps, Educational Contents, Multi Layer Perceptron, Particle Swarm Optimization (pso) | |
| dc.subject | Artificial intelligence, Education, Educational technology, Feature extraction, Hybrid systems, Information systems, Swarm intelligence, Concept detection, Concept maps, Educational contents, Multi layer perceptron, Particle swarm optimization (PSO) | |
| dc.title | A feature selection application using particle swarm optimization for learning concept detection | |
| dc.type | Conference Object | |
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| oaire.citation.endPage | 962 | |
| oaire.citation.startPage | 952 | |
| person.identifier.scopus-author-id | Günel- Korhan (23396908400), Erdoǧdu- Kazım (57194068583), Polat- Refet (54401461400), Ozarslan- Yasin (37161863700) | |
| project.funder.name | We would like to acknowledge support for this study from the Scientific and Technological Research Council of Turkey (TÜBİTAK) 3501 - National Young Researcher Career Development Program (CAREER) project under Grant no. 3501-115E472. | |
| publicationvolume.volumeNumber | 570 | |
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