Design and development of a custom system of technology surveillance and competitive intelligence in SMEs

Making 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.

• Autores: Silva, Jesus; Vidal Pacheco, Lucelys del Carmen; Parra Negrete, Kevin; Combita Niño, Johana Patricia; Pineda Lezama, Omar Bonerge; Izquierdo Varela, Noel
• Tipo de recurso: Article of journal
• Fecha de publicación: 2019
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/4838
• Acceso en línea: https://hdl.handle.net/11323/4838; https://repositorio.cuc.edu.co/
• Palabra clave: Web mining; technology surveillance and competitive intelligence; decision making; advanced cluster vector page ranking
• Rights: openAccess
• License: Attribution-NonCommercial-NoDerivatives 4.0 International