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dc.contributor.authorKulvietis, Genadijus
dc.contributor.authorMamčenko, Jelena
dc.contributor.authorŠileikienė, Irma
dc.date.accessioned2023-09-18T19:40:01Z
dc.date.available2023-09-18T19:40:01Z
dc.date.issued2006
dc.identifier.issn1790-1979
dc.identifier.other(BIS)VGT02-000013234
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/142059
dc.description.abstractDistance education is organised in three main forms: asynchronous, synchronous and blended. Student's data for analysis will be used only the asynchronous learning portion of the information system, since this portion is already used in master's studies for a considerable time, and a sufficient amount of data has been accumulated. Data mining technology can help to find interesting and useful patterns in huge volume of data. Data analysis will be performed on the data of master students and bachelor students as well, that can learn in 11 e-courses. Clustering technique was used for user's data analysis which is fitting best when we know nothing about them. After clustering database we have got nine clusters and that's clusters' interpretation, which let us to except typical student's behaviours.eng
dc.format.extentp. 1482-1488
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyCompendex
dc.titleData mining application for distance education information system
dc.typeStraipsnis kitoje DB / Article in other DB
dcterms.references10
dc.type.pubtypeS3 - Straipsnis kitoje DB / Article in other DB
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.enE-learning
dc.subject.enAsynchronous learning
dc.subject.enInformation system
dc.subject.enData mining
dc.subject.enIntelligent mining
dcterms.sourcetitleWSEAS transactions on information science and applications
dc.description.issueiss. 8
dc.description.volumeVol. 3
dc.publisher.nameWSEAS
dc.publisher.cityAthens
dc.identifier.elaba3752467


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