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dc.contributor.authorKarami, Amin
dc.contributor.authorGuerrero Zapata, Manel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2015-02-06T09:40:01Z
dc.date.available2015-02-06T09:40:01Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationKarami, A.; Guerrero, M. Mining and visualizing uncertain data objects and named data networking traffics by fuzzy self-organizing map. A: International Workshop on Artificial Intelligence and Cognition. "Proceedings of the Second International Workshop on Artificial Intelligence and Cognition (AIC 2014): Torino, Italy, November 26-27, 2014". Torino: CEUR-WS.org, 2014, p. 156-163.
dc.identifier.isbn1613-0073
dc.identifier.urihttp://hdl.handle.net/2117/26239
dc.description.abstractUncertainty is widely spread in real-world data. Uncertain data-in computer science-is typically found in the area of sensor networks where the sensors sense the environment with certain error. Mining and visualizing uncertain data is one of the new challenges that face uncertain databases. This paper presents a new intelligent hybrid algorithm that applies fuzzy set theory into the context of the Self-Organizing Map to mine and visualize uncertain objects. The algorithm is tested in some benchmark problems and the uncertain traffics in Named Data Networking (NDN). Experimental results indicate that the proposed algorithm is precise and effective in terms of the applied performance criteria.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherCEUR-WS.org
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
dc.subject.lcshSensor networks
dc.subject.lcshUncertainty -- Mathematical models
dc.subject.otherAlgorithms
dc.subject.otherArtificial intelligence
dc.subject.otherConformal mapping
dc.subject.otherFuzzy sets
dc.subject.otherSelf organizing maps
dc.subject.otherBench-mark problems
dc.subject.otherFuzzy self-organizing maps
dc.subject.otherHybrid algorithms
dc.subject.otherNamed data networkings
dc.subject.otherPerformance criterion
dc.subject.otherReal-world
dc.subject.otherUncertain database
dc.subject.otherUncertain datas
dc.titleMining and visualizing uncertain data objects and named data networking traffics by fuzzy self-organizing map
dc.typeConference report
dc.subject.lemacXarxes de sensors
dc.subject.lemacIncertesa -- Models matemàtics
dc.contributor.groupUniversitat Politècnica de Catalunya. CNDS - Xarxes de Computadors i Sistemes Distribuïts
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ceur-ws.org/Vol-1315/paper14.pdf
dc.rights.accessOpen Access
local.identifier.drac15413751
dc.description.versionPostprint (published version)
local.citation.authorKarami, A.; Guerrero, M.
local.citation.contributorInternational Workshop on Artificial Intelligence and Cognition
local.citation.pubplaceTorino
local.citation.publicationNameProceedings of the Second International Workshop on Artificial Intelligence and Cognition (AIC 2014): Torino, Italy, November 26-27, 2014
local.citation.startingPage156
local.citation.endingPage163


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain