Desarrollo de un sistema de recomendación para artículos de revistas científicas abiertas utilizando tecnologías de datos enlazados.

Abstract

At present there are a lot of open access linked data repositories, which are available for use by those who need to share and get information in different fields. But the use of linked data has been limited by the difficulty of extracting content from a set of articles. These limitations fall on those who are not familiar with the linked data technologies, since nowadays there are few tools which allow a friendly interaction, and it’s even more difficult to find a reference management software that includes: an advanced search, library of references and quotes generation. In this article, we present an architecture for a scientific article recommendation system using data from linked data repositories and their quotations. The architecture works as a base for the development of a recommendation web system that was developed and tested. With the final product, an evaluation of the results and recommendations from the system is carried out based on the search. Similarly, the techniques of extraction, search and data storage are presented along with the diagrams, algorithms and tools used.