SciELO - Scientific Electronic Library Online

 
vol.26 número1Methodology for Identification and Classifying of Cybercrime on Tor Network through the Use of Cryptocurrencies Based on Web Textual ContentsDistraction Detection to Predict Vehicle Crashes: a Deep Learning Approach índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares en SciELO

Compartir


Computación y Sistemas

versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546

Resumen

MORALES MURILLO, Víctor Giovanni; PINTO AVENDANO, David Eduardo; ROJAS LOPEZ, Franco  y  GONZALES CALLEROS, Juan Manuel. A Systematic Literature Review on the Hybrid Approaches for Recommender Systems. Comp. y Sist. [online]. 2022, vol.26, n.1, pp.357-372.  Epub 08-Ago-2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-1-4180.

Recommender systems represent a high economic, social, and technological impact at international level due to the most relevant technological companies have been used them as their main services considering that user experience and companies sales have been improved. For this reason, these systems are a principal research area, and the companies optimize their algorithms with hybrid approaches that combine two or more recommendation strategies. A systematic literature review on the hybrid approaches for recommender systems is generated by this work, the objectives are to analyze research line progress and to identify opportunity areas for future investigations. Further, the recent trends about challenges, methodologies, datasets, application domains and evaluation metrics on hybrid approach are identified. An art state from 2016 to 2020 is developed with information systems guide than unlike others works that use less recent guide and software engineering guide. This research will benefit recommender systems community.

Palabras llave : Recommender systems; hybrid approaches; systematic literature review; information systems; hybrid recommender systems art state.

        · texto en Inglés