Open AccessProposal of a simple recommendation system for small and medium enterprises for decision making based on unsupervised learning
Author(s) -
Daniel Urueta,
Pedro Lara-Velázquez,
Miguel Ángel Gutiérrez Andrade,
Sergio G. De los Cobos-Silva
Publication year - 2019
Publication title -
revista de estrategias del desarrollo empresarial
Language(s) - English
Resource type - Journals
ISSN - 2444-4960
DOI - 10.35429/jbds.2019.15.5.9.13
Subject(s) - computer science , disadvantage , artificial intelligence , robustness (evolution) , machine learning , task (project management) , simple (philosophy) , engineering , biochemistry , chemistry , philosophy , systems engineering , epistemology , gene
Recommendation systems are generally complicated, due they search to increase their reach and robustness, they combine different artificial intelligence approaches mainly of supervised learning. A disadvantage of this type of systems is that they must have a prior classification to be able to train a system and after they can be able to make decisions in a simmilar way that a human would do it; however, the task of classification is often expensive because is needed to consult with experts the possible classification (also known as label) that should be given to a specific data; although this method can be profitable for large companies, it is not for small and medium companies. This is the reason which the present work shows a proposal of a simple system that does not need to have a previous classification, allowing it to be profitable for small and medium enterprises in decision making.