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Referrer Graph: A cost-effective algorithm and pruning method for predicting web accesses

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Referrer Graph: A cost-effective algorithm and pruning method for predicting web accesses

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dc.contributor.author De La Ossa Perez, Bernardo Antonio es_ES
dc.contributor.author Gil Salinas, José Antonio es_ES
dc.contributor.author Sahuquillo Borrás, Julio es_ES
dc.contributor.author Pont Sanjuan, Ana es_ES
dc.date.accessioned 2014-10-14T11:31:53Z
dc.date.available 2014-10-14T11:31:53Z
dc.date.issued 2013-05
dc.identifier.issn 0140-3664
dc.identifier.uri http://hdl.handle.net/10251/43243
dc.description.abstract This paper presents the Referrer Graph (RG) web prediction algorithm and a pruning method for the associated graph as a low-cost solution to predict next web users accesses. RG is aimed at being used in a real web system with prefetching capabilities without degrading its performance. The algorithm learns from users accesses and builds a Markov model. These kinds of algorithms use the sequence of the user accesses to make predictions. Unlike previous Markov model based proposals, the RG algorithm differentiates dependencies in objects of the same page from objects of different pages by using the object URI and the referrer in each request. Although its design permits us to build a simple data structure that is easier to handle and, consequently, needs lower computational cost in comparison with other algorithms, a pruning mechanism has been devised to avoid the continuous growing of this data structure. Results show that, compared with the best prediction algorithms proposed in the open literature, the RG algorithm achieves similar precision values and page latency savings but requiring much less computational and memory resources. Furthermore, when pruning is applied, additional and notable resource consumption savings can be achieved without degrading original performance. In order to reduce further the resource consumption, a mechanism to prune de graph has been devised, which reduces resource consumption of the baseline system without degrading the latency savings. 2013 Elsevier B.V. All rights reserved. es_ES
dc.description.sponsorship This work has been partially supported by Spanish Ministry of Science and Innovation under Grant TIN2009-08201. The authors would also like to thank the technical staff of the School of Computer Science at the Polytechnic University of Valencia for providing us recent and customized trace files logged by their web server. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Innovation [TIN2009-08201] es_ES
dc.relation.ispartof Computer Communications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Web prediction and prefetching es_ES
dc.subject Prediction algorithm es_ES
dc.subject Web latency reduction es_ES
dc.subject Performance evaluation es_ES
dc.subject Measurement es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Referrer Graph: A cost-effective algorithm and pruning method for predicting web accesses es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.comcom.2013.02.005
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/287759/EU en_EN
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Economía y Ciencias Sociales - Departament d'Economia i Ciències Socials es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation De La Ossa Perez, BA.; Gil Salinas, JA.; Sahuquillo Borrás, J.; Pont Sanjuan, A. (2013). Referrer Graph: A cost-effective algorithm and pruning method for predicting web accesses. Computer Communications. 36(8):881-894. https://doi.org/10.1016/j.comcom.2013.02.005 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.comcom.2013.02.005 es_ES
dc.description.upvformatpinicio 881 es_ES
dc.description.upvformatpfin 894 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 36 es_ES
dc.description.issue 8 es_ES
dc.relation.senia 253399


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