Analysis of Different Proposals to Improve the Dissemination of Information in University Digital Libraries
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.
KeywordsDigital libraries Dissemination of information Recommender systems Fuzzy linguistic modelling
This paper has been developed with the financing of Projects TIN2013-40658-P and TIN2016-75850-R.
- 3.Burke, R.: Hybrid web recommender systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web, LNCS, vol. 4321, pp. 377–408 (2007)Google Scholar
- 6.Callan, J., Smeaton, A.: Personalization and recommender systems in digital libraries. In: Joint NSF-EU DELOS Working Group Report (2003)Google Scholar
- 8.Charlotte-Ahrens, S.: Recommender Systems: Relevance in the Consumer Purchasing Process. Epubli, Berlin (2011)Google Scholar
- 13.Korfhage, R.: Information Storage and Retrieval. Wiley Computer Publishing, New York (1997)Google Scholar
- 14.Marchionini, G.: Research and development in digital libraries (2000). http://ils.unc.edu/~march/digital_library_R_and_D.html
- 18.Montoya, R.: Boundary objects/boundary staff: Supporting digital scholarship in academic libraries. J. Acad. Librarianship (2017, in press)Google Scholar
- 25.Shannon, A., Orozova, D., Sotirova, E., Atanassov, K., Melo-Pinto, P., Kim, T.: Generalized net model of a university electronic library, using intuitionistic fuzzy estimations. In: Proceedings of the Eight International Conference on Intuitionistic Fuzzy Sets, vol. 10, pp. 91–96 (2004)Google Scholar
- 26.Shannon, A., Rieçan, B., Sotirova, E., Inovska, G., Atanassov, K., Krawczak, M., Melo-Pinto, P., Kim, T.: A generalized net model of university subjects rating with intuitionistic fuzzy estimations. Notes on Intuitionistic Fuzzy Sets 18, 61–67 (2012)Google Scholar
- 29.Zadeh, L.: The concept of a linguistic variable and its applications to approximate reasoning. Part I, Inf. Sci. 8, 199–249 (1975), Part II, Inf. Sci. 8, 301–357 (1975), Part III. Inf. Sci. 9, 43–80 (1975)Google Scholar