A knowledge-based multi-criteria collaborative filtering approach for discovering services in mobile cloud computing platforms

The case of MobiCloUP!
  • Luis Omar Colombo-Mendoza
  • Rafael Valencia-García
  • Ricardo Colomo-Palacios
  • Giner Alor-Hernández


In the context of Cloud-based development of mobile applications, third-party services to be integrated by applications often have to be manually selected among many categories and providers at design time. Over the years, recommender systems have proven effective in overcoming the challenges related to the incredible growth of the information on the Web. In an effort to better address this problem, the use of Semantic Web technologies in the development of recommender systems has been gaining momentum in recent years. In this paper, we propose a knowledge-based Collaborative Filtering recommendation approach for the discovery of services in a mobile Cloud computing platform for services-based development. Our approach employs a knowledge-based technique that takes advantage of Semantic Web rule-based reasoning capabilities. A major contribution of this work is a multi-criteria collaborative service evaluation mechanism that is based on a standard service quality framework and is built on top of an ontology-based domain model. A two-part evaluation method that is intended to evaluate the proposed recommendation approach not only from a Computer Science perspective but also from an Information Systems perspective is also presented.


Recommender system Multi-criteria rating Collaborative filtering Semantic web Knowledge base Mobile cloud computing 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Facultad de InformáticaUniversidad de Murcia, Campus de EspinardoMurciaSpain
  2. 2.División de Estudios de Posgrado e Investigación, Instituto Tecnológico de OrizabaOrizabaMéxico

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