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An Efficient and Scalable Recommender System for the Smart Web

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorBaldominos Gómez, Alejandro
dc.contributor.authorSáez Achaerandio, Yago
dc.contributor.authorAlbacete García, Esperanza
dc.contributor.authorMarrero, Ignacio
dc.date.accessioned2016-02-17T11:56:53Z
dc.date.available2016-02-17T11:56:53Z
dc.date.issued2015-11-01
dc.descriptionThis proceeding at: 11th International Conference on Innovations in Information Technology (IIT) Innovations 2015. Special Theme: Smart Cities, Big Data, Sustainable Development. Took place at 2015, November, 01 - 03, in Dubai, United Arab Emirates (IEEE IIT 2015).en
dc.description.abstractThis work describes the development of a web recommender system implementing both collaborative filtering and content-based filtering. Moreover, it supports two different working modes, either sponsored or related, depending on whether websites are to be recommended based on a list of ongoing ad campaigns or in the user preferences. Novel recommendation algorithms are proposed and implemented, which fully rely on set operations such as union and intersection in order to compute the set of recommendations to be provided to end users. The recommender system is deployed over a real-time big data architecture designed to work with Apache Hadoop ecosystem, thus supporting horizontal scalability, and is able to provide recommendations as a service by means of a RESTful API. The performance of the recommender is measured, resulting in the system being able to provide dozens of recommendations in few milliseconds in a single-node cluster setup.en
dc.description.sponsorshipThis research work is part of Memento Data Analysis project, co-funded by the Spanish Ministry of Industry, Energy and Tourism with no. TSI-020601-2012-99 and TSI-020110-2009-137.en
dc.description.statusPublicado
dc.format.extent6
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationProceedings of the 2015. 11th International Conference on Innovations in Information Technology (IIT). Innovations 2015. Special Theme: Smart Cities, Big Data, Sustainable Development, pp. 296-301.en
dc.identifier.isbn978-1-4673-8509-1
dc.identifier.publicationfirstpage296
dc.identifier.publicationlastpage301
dc.identifier.publicationtitleProceedings of the 2015 11th International Conference on Innovations in Information Technology (IIT). Innovations 2015. Special Theme: Smart Cities, Big Data, Sustainable Development.en
dc.identifier.publicationvolume2015
dc.identifier.urihttps://hdl.handle.net/10016/22318
dc.identifier.uxxiCC/0000024136
dc.language.isoeng
dc.publisherIEEE. Computer Societyen
dc.relation.eventdate2015 November, 01-03en
dc.relation.eventnumber11
dc.relation.eventplaceDubai (EEAU)en
dc.relation.eventtitleInternational Conference on Innovations in Information Technology (IIT) Innovations 2015. (IEEE IIT 2015).en
dc.relation.ispartofseriesInnovations in Information Technology/2015en
dc.relation.projectIDGobierno de España. TSI-020110-2009-137es
dc.relation.projectIDGobierno de España. TSI-020601-2012-99es
dc.relation.publisherversionhttp://dx.doi.org/10.1109/INNOVATIONS.2015.7381557
dc.rights© 2015, IEEEen
dc.rights.accessRightsopen access
dc.subject.ecienciaInformáticaes
dc.subject.otherAlgorithm design and analysisen
dc.subject.otherBig dataen
dc.subject.otherCollaborationen
dc.subject.otherComputer architectureen
dc.subject.otherReal-time systemsen
dc.subject.otherRecommender systemsen
dc.subject.otherAmart Citiesen
dc.subject.otherUniform resource locators.en
dc.titleAn Efficient and Scalable Recommender System for the Smart Weben
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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