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dc.contributorTous Liesa, Rubén
dc.contributorTorres Viñals, Jordi
dc.contributor.authorSulca Correa, Omar Iván
dc.date.accessioned2015-05-05T15:23:42Z
dc.date.available2015-05-05T15:23:42Z
dc.date.issued2015-04-28
dc.identifier.urihttp://hdl.handle.net/2099.1/25961
dc.description.abstractThe Big data analysis has becoming increasingly more relevant for the enterprises because the efficient handling of information represents a unique competitive advantage, being its application so diverse as the nature of the data. Ejm. Fraud detection, advertising strategies, web traffic m onitoring, etc. Apache Spark is a engine for large - scale data processing, intended to be a drop in replacement for Hadoop MapReduce providing the benefit of improved performance; the main goal of this project is proof the capabilities of this system, throu gh the development and implementation of a distributed pipeline for processing and indexing at high speed and real - time multimedia data streams generated by social networks and detect trends in these, using for this purpose the Spark related projects and l ibraries: Spark Streaming and Spark MLlib. To verify the effectiveness of the algorithm, different benchmarks (with different configurations) will be performed, these results will be analyzed.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Infraestructures i modelització dels transports::Trànsit
dc.subjectÀrees temàtiques de la UPC::Informàtica::Sistemes d'informació
dc.subject.lcshBig data
dc.subject.otherSpark
dc.subject.otherLDA
dc.subject.otherstreaming
dc.subject.otherclustering
dc.titleMultimedia big data computing for trend detection
dc.typeMaster thesis
dc.subject.lemacMacrodades
dc.identifier.slug106081
dc.rights.accessOpen Access
dc.date.updated2015-05-01T04:00:16Z
dc.audience.educationlevelMàster
dc.audience.mediatorFacultat d'Informàtica de Barcelona
dc.audience.degreeMÀSTER UNIVERSITARI EN ENGINYERIA INFORMÀTICA (Pla 2012)


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