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dc.creatorSilva, Jesus
dc.creatorVidal Pacheco, Lucelys del Carmen
dc.creatorParra Negrete, Kevin
dc.creatorCombita Niño, Johana Patricia
dc.creatorPineda Lezama, Omar Bonerge
dc.creatorIzquierdo Varela, Noel
dc.date.accessioned2019-06-10T13:54:33Z
dc.date.available2019-06-10T13:54:33Z
dc.date.issued2019
dc.identifier.issn0000-2010
dc.identifier.urihttp://hdl.handle.net/11323/4838
dc.description.abstractMaking strategic decisions is a complex process that requires reliable and up-to-date information. It is therefore necessary to have tools that facilitate the information management. Technology Surveillance (TS) and Competitive Intelligence (CI) are two disciplines that seek to obtain accurate and up-to-date information. Clearly, the web is the largest and most important source of information, but their destructuring and disorganization requires tools that help to manage it. This work presents a model for TS and CI using Web Mining techniques such as ranking algorithm of web pages based on machine learning, i.e. the Advanced Cluster Vector Page Ranking (ACVPR) algorithm.es_ES
dc.language.isoenges_ES
dc.publisherProcedia Computer Sciencees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectWeb mininges_ES
dc.subjecttechnology surveillance and competitive intelligencees_ES
dc.subjectdecision makinges_ES
dc.subjectadvanced cluster vector page rankinges_ES
dc.titleDesign and development of a custom system of technology surveillance and competitive intelligence in SMEses_ES
dc.typeArticlees_ES
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