Analysis of Different Proposals to Improve the Dissemination of Information in University Digital Libraries

  • Carlos Porcel
  • Alberto Ching-López
  • Alvaro Tejeda-Lorente
  • Juan Bernabé-Moreno
  • Enrique Herrera-Viedma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 643)

Abstract

Currently the great advances in Web technologies are changing the process of access to information and the Web is one of the most important source of information. Furthermore, the Web influences the development of others media, for example, newspapers, journals, books, libraries, etc. In this paper we analyze its impact in the development of the university digital libraries. As well as on the Web, the information growth is a big problem for academic digital libraries, and similar tools can be applied in university digital libraries to provide users with access to the information. Given the importance of this aspect, in this paper we analyze and review different proposals that improve the processes of dissemination of information in these university digital libraries, promoting access to information of interest. These proposals manage to adapt access to information according to the needs and preferences of each user. As we can see in the literature, one of the techniques with the best results, is the application of recommender systems. Recommender systems are tools whose objective is to evaluate and filter the large amount of information available on the Web to assist users in their process of access to information. Thus, in this paper we analyze some proposals based on recommender system to help students, teachers and researchers to find research resources that can improve the services provided by the university digital libraries.

Keywords

Digital libraries Dissemination of information Recommender systems Fuzzy linguistic modelling 

Notes

Acknowledgments

This paper has been developed with the financing of Projects TIN2013-40658-P and TIN2016-75850-R.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Carlos Porcel
    • 1
  • Alberto Ching-López
    • 2
  • Alvaro Tejeda-Lorente
    • 2
  • Juan Bernabé-Moreno
    • 2
  • Enrique Herrera-Viedma
    • 2
  1. 1.Department of Computer ScienceUniversity of JaénJaénSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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