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dc.contributor.authorCarmen De Maio
dc.contributor.authorGiuseppe Fenza
dc.contributor.authorMatteo Gaeta
dc.contributor.authorVincenzo Loia
dc.contributor.authorFrancesco Orciuoli
dc.contributor.authorSabrina Senatore
dc.date.accessioned2019-09-25T17:02:17Z
dc.date.available2019-09-25T17:02:17Z
dc.date.created2018-05-28 23:07
dc.date.issued2012
dc.identifieroai:www.iris.unisa.it:11386/3095062
dc.identifierhttp://hdl.handle.net/11386/3095062
dc.identifier10.1016/j.asoc.2011.09.004
dc.identifier2-s2.0-81155133554
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S1568494611003826
dc.identifier.urihttp://hdl.handle.net/20.500.12424/363390
dc.description.abstractNowadays, Web 2.0 focuses on user generated content, data sharing and collaboration activities. Formats like Really Simple Syndication (RSS) provide structured Web information, display changes in summary form and stay updated about news headlines of interest. This trend has also affected the e-learning domain, where RSS feeds demand for dynamic learning activities, enabling learners and teachers to access to new blog posts, to keep track of new shared media, to consult Learning Objects which meet their needs. 
 
 This paper presents an approach to enrich personalized e-learning experiences with user-generated content, through a contextualized RSS-feeds fruition. The synergic exploitation of Knowledge Modeling and Formal Concept Analysis techniques enables the design and development of a system that supports learners in their learning activities by collecting, conceptualizing, classifying and providing updated information on specific topics coming from relevant information sources. An agent-based layer supervises the extraction and filtering of RSS feeds whose topics cover a specific educational domain.
dc.language.isoeng
dc.relation.ispartofinfo:eu-repo/semantics/altIdentifier/wos/WOS:000296986100011
dc.relation.ispartofinfo:eu-repo/semantics/altIdentifier/hdl/11386/3095062
dc.relation.ispartofAPPLIED SOFT COMPUTING
dc.relation.ispartofurn:ISSN:1568-4946
dc.subjectKnowledge Modeling, e-Learning, Web 2.0, Fuzzy logic, Formal Concept Analysis, Agent-based system, Web
dc.subjectInformation Retrieval
dc.titleRSS-based e-learning recommendations exploiting fuzzy FCA for Knowledge Modeling
dc.typeinfo:eu-repo/semantics/article
ge.collectioncodeEC
ge.dataimportlabelOAI metadata object
ge.identifier.legacyglobethics:14600594
ge.identifier.permalinkhttps://www.globethics.net/gel/14600594
ge.lastmodificationdate2018-05-28 23:07
ge.lastmodificationuseradmin@pointsoftware.ch (import)
ge.submissions0
ge.oai.exportid149104
ge.oai.repositoryid100371
ge.oai.setname1 Contributo su Rivista
ge.oai.setnameCatalogo Prodotti Ricerca
ge.oai.setname1.1.2 Articolo su rivista con ISSN
ge.oai.setspeccom_11386_4642509
ge.oai.setspeccom_11386_4642508
ge.oai.setspeccol_11386_4642460
ge.oai.streamid2
ge.setnameGlobeEthicsLib
ge.setspecglobeethicslib
ge.linkhttp://hdl.handle.net/11386/3095062
ge.linkhttp://www.sciencedirect.com/science/article/pii/S1568494611003826


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