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Crowdsourced Recommender System

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Crowdsourced Recommender System

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dc.contributor.author Montebello, Matthew es_ES
dc.contributor.author Mallia Milanes, Mario es_ES
dc.date.accessioned 2018-10-05T13:15:39Z
dc.date.available 2018-10-05T13:15:39Z
dc.date.issued 2018-07-02T13:15:39Z
dc.identifier.isbn 9788490486900 es_ES
dc.identifier.uri http://hdl.handle.net/10251/109677
dc.description.abstract [EN] The use of artificially intelligent techniques to overcome specific shortcomings within e-learning systems is a well-researched area that keeps on evolving in an attempt to optimise such resourceful practices. The lack of personalization and the sentiment of isolation coupled with a feeling of being treated like all others, tends to discourage and push learners away from courses that are very well prepared academically and excellently projected intellectually. The use of recommender systems to deliver relevant information in a timely manner that is specifically differentiated to a unique learner is once more being investigated to alievate the e-learning issue of being impersonal.  The application of such a technique also assists the learner by reducing information overload and providing learning material that can be shared, criticized and reviewed at one’s own pace. In this paper we propose the use of a fully automated recommender system based on recent AI developments together with Web 2.0 applications and socially networked technologies. We argue that such technologies have provided the extra capabilities that were required to deliver a realistic and practical interfacing medium to assist online learners and take recommender systems to the next level. es_ES
dc.description.uri http://ocs.editorial.upv.es/index.php/HEAD/HEAD18 es_ES
dc.format.extent 7
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation.ispartof 4th International Conference on Higher Education Advances (HEAD'18)
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Higher Education es_ES
dc.subject Learning es_ES
dc.subject Educational systems es_ES
dc.subject Teaching es_ES
dc.subject Artificial intelligence
dc.subject E-learning
dc.subject Recommender system
dc.subject Collaborative
dc.subject Crowdsource
dc.title Crowdsourced Recommender System es_ES
dc.type Comunicación en congreso es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.4995/HEAD18.2018.8020 es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Montebello, M.; Mallia Milanes, M. (2018). Crowdsourced Recommender System. Editorial Universitat Politècnica de València. 497-503. https://doi.org/10.4995/HEAD18.2018.8020 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename Fourth International Conference on Higher Education Advances es_ES
dc.relation.conferencedate Junio 20-22,2018 es_ES
dc.relation.conferenceplace Valencia, Spain es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/HEAD/HEAD18/paper/view/8020 es_ES
dc.description.upvformatpinicio 497
dc.description.upvformatpfin 503
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\8020 es_ES


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