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dc.contributor.authorBeel, J.en
dc.contributor.authorLanger, S.en
dc.contributor.authorKapitsaki, Georgia M.en
dc.contributor.authorBreitinger, C.en
dc.contributor.authorGipp, B.en
dc.contributor.editorBontcheva K.en
dc.contributor.editorRicci F.en
dc.contributor.editorConlan O.en
dc.contributor.editorLawless S.en
dc.creatorBeel, J.en
dc.creatorLanger, S.en
dc.creatorKapitsaki, Georgia M.en
dc.creatorBreitinger, C.en
dc.creatorGipp, B.en
dc.date.accessioned2019-11-13T10:38:25Z
dc.date.available2019-11-13T10:38:25Z
dc.date.issued2015
dc.identifier.issn0302-9743
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/53614
dc.description.abstractMind maps have not received much attention in the user modeling and recommender system community, although mind maps contain rich information that could be valuable for user-modeling and recommender systems. In this paper, we explored the effectiveness of standard user-modeling approaches applied to mind maps. Additionally, we develop novel user modeling approaches that consider the unique characteristics of mind maps. The approaches are applied and evaluated using our mind mapping and reference-management software Docear. Docear displayed 430,893 research paper recommendations, based on 4,700 user mind maps, from March 2013 to August 2014. The evaluation shows that standard user modeling approaches are reasonably effective when applied to mind maps, with click-through rates (CTR) between 1.16% and 3.92%. However, when adjusting user modeling to the unique characteristics of mind maps, a higher CTR of 7.20% could be achieved. A user study confirmed the high effectiveness of the mind map specific approach with an average rating of 3.23 (out of 5), compared to a rating of 2.53 for the best baseline. Our research shows that mind map-specific user modeling has a high potential, and we hope that our results initiate a discussion that encourages researchers to pursue research in this field and developers to integrate recommender systems into their mind mapping tools. © Springer International Publishing Switzerland 2015.en
dc.source23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84937468593&doi=10.1007%2f978-3-319-20267-9_1&partnerID=40&md5=3118d0ff82b0b171a0fc98c2a2b11b49
dc.subjectMappingen
dc.subjectHigh potentialen
dc.subjectClick-through rateen
dc.subjectMind mapen
dc.subjectMind mapsen
dc.subjectMind-mappingen
dc.subjectRecommender systemsen
dc.subjectReference management softwaresen
dc.subjectResearch papersen
dc.subjectSchematic diagramsen
dc.subjectUser modelingen
dc.subjectUser studyen
dc.titleExploring the potential of user modeling based on mind mapsen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1007/978-3-319-20267-9_1
dc.description.volume9146
dc.description.startingpage3
dc.description.endingpage17
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Sponsors: Foundation, NSFen
dc.description.notesGoogleen
dc.description.notesMicrosoften
dc.description.notesScience Foundation Ireland, sfien
dc.description.notesU.S. National Scienceen
dc.description.notesUser Modeling Inc., UMen
dc.description.notesConference code: 119109en
dc.description.notesCited By :2</p>en
dc.source.abbreviationLect. Notes Comput. Sci.en
dc.contributor.orcidKapitsaki, Georgia M. [0000-0003-3742-7123]
dc.gnosis.orcid0000-0003-3742-7123


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