Personalized links recommendation based on data mining in adaptive educational hypermedia systems

C. Romero, S. Ventura, J.A. Delgado, P.M.E. De Bra

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    54 Citations (Scopus)

    Abstract

    In this paper, we describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable educational hypermedia system. We present a specific mining tool and a recommender engine that we have integrated in the AHA! system in order to help the teacher to carry out the whole web mining process. We report on several experiments with real data in order to show the suitability of using both clustering and sequential pattern mining algorithms together for discovering personalized recommendation links.
    Original languageEnglish
    Title of host publicationProceedings of the 2nd European Conference on Technology Enhanced Learning: Creating New Learning Experiences on a Global Scale (EC-TEL 2007) 17-20 September 2007, Crete, Greece
    EditorsE. Duval, R. Klamma, M. Wolpers
    Place of PublicationBerlin, Germany
    PublisherSpringer
    Pages292-306
    ISBN (Print)978-3-540-75194-6
    DOIs
    Publication statusPublished - 2007
    Eventconference; EC-TEL 2007, Crete, Greece; 2007-09-17; 2007-09-20 -
    Duration: 17 Sep 200720 Sep 2007

    Publication series

    NameLecture Notes in Computer Science
    Volume4753
    ISSN (Print)0302-9743

    Conference

    Conferenceconference; EC-TEL 2007, Crete, Greece; 2007-09-17; 2007-09-20
    Period17/09/0720/09/07
    OtherEC-TEL 2007, Crete, Greece

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