Integración de los algoritmos knn y fp-growth para apoyar la gestión de relaciones con clientes

The organizations extremely are competitive surroundings, in which the administration of the relations with the clients acquires a signicant, especially in the related thing to the loyalty, the increase of the sales and the increase of the yield. Consequently, the organizations are called to admini...

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Autores:
Mejía Goyeneche, juan sebastián
Estrada Esponda, Royer David
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Santo Tomás
Repositorio:
Universidad Santo Tomás
Idioma:
spa
OAI Identifier:
oai:repository.usta.edu.co:11634/15818
Acceso en línea:
http://revistas.ustatunja.edu.co/index.php/ingeniomagno/article/view/1644
Palabra clave:
CRM
FP-GROWTH
Intelligence of Businesses
SCRUM
KNN
CRM
FP-GROWTH
Inteligencia de Negocios
SCRUM
KNN
CRM
FP-GROWTH
Inteligência de Negócios
SCRUM
KNN
Rights
License
Derechos de autor 2019 Ingenio Magno
Description
Summary:The organizations extremely are competitive surroundings, in which the administration of the relations with the clients acquires a signicant, especially in the related thing to the loyalty, the increase of the sales and the increase of the yield. Consequently, the organizations are called to administer the relations with their clients from the strategic point of view, but also from the tactical and operative point of view. By such reason, the technology is one of those components that such management supports and that its effective implementation potentialises. The present article sets out the results of a degree project, that approached problematic concerning the management of relations with the clients in a restaurant of fast meals of Tuluá, based on the methodology the SCRUM and techniques of mining of data, the result was a computer science system for the support to the decision making in the context of the intelligence of businesses. The integration of the algorithms of near neighbors (KNN) and FP-GROWTH stands out, with the purpose of emitting recommendations in relation to the preferences of the consumers with base in the composition of products more consumed by them. In addition, once integrated the algorithms they tried on in four different scenes, which allowed to conclude that such integration does not have associate a high computer cost.