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Real-Time Prediction of Gamers Behavior Using Variable Order Markov and Big Data Technology: A Case of Study

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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.authorAlbacete García, Esperanza
dc.contributor.authorMarrero, Ignacio
dc.contributor.authorSáez Achaerandio, Yago
dc.date.accessioned2016-03-09T10:09:43Z
dc.date.available2016-03-09T10:09:43Z
dc.date.issued2016-03
dc.description.abstractThis paper presents the results and conclusions found when predicting the behavior of gamers in commercial videogames datasets. In particular, it uses Variable-Order Markov (VOM) to build a probabilistic model that is able to use the historic behavior of gamers and to infer what will be their next actions. Being able to predict with accuracy the next user's actions can be of special interest to learn from the behavior of gamers, to make them more engaged and to reduce churn rate. In order to support a big volume and velocity of data, the system is built on top of the Hadoop ecosystem, using HBase for real-time processing; and the prediction tool is provided as a service (SaaS) and accessible through a RESTful API. The prediction system is evaluated using a case of study with two commercial videogames, attaining promising results with high prediction accuracies.en
dc.description.sponsorshipThis work is part of Memento Data Analysis project, co-funded by the Spanish Ministry of Industry, Energy and Tourism with identifier TSI-020601-2012-99 and is supported by the Spanish Ministry of Education, Culture and Sport through FPU fellowship with identifier FPU13/03917en
dc.format.extent8
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationBaldominos, A. et al. 2016. Real-Time Prediction of Gamers Behavior Using Variable Order Markov and Big Data Technology: A Case of Study. International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 3, n.6en
dc.identifier.doi10.9781/ijimai.2016.367
dc.identifier.issn1989-1660
dc.identifier.publicationfirstpage44
dc.identifier.publicationissue6
dc.identifier.publicationlastpage51
dc.identifier.publicationtitleInternational Journal of Interactive Multimedia and Artificial Intelligenceen
dc.identifier.publicationvolume3
dc.identifier.urihttps://hdl.handle.net/10016/22491
dc.identifier.uxxiAR/0000017716
dc.language.isoengen
dc.publisherIMAI Software Research Groupen
dc.relation.projectIDGobierno de España.TSI-020601-2012-99es
dc.relation.publisherversionhttps://doi.org/10.9781/ijimai.2016.367
dc.rights© 2014 The Authors.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherUser behavioren
dc.subject.otherPredictionen
dc.subject.otherVariable-order markoven
dc.subject.otherBig dataen
dc.subject.otherReal-Timeen
dc.titleReal-Time Prediction of Gamers Behavior Using Variable Order Markov and Big Data Technology: A Case of Studyen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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