Personalized Access to Scientific Publications: from Recommendation to Explanation

  • Dario De Nart
  • Felice Ferrara
  • Carlo Tasso
Conference paper

DOI: 10.1007/978-3-642-38844-6_26

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7899)
Cite this paper as:
De Nart D., Ferrara F., Tasso C. (2013) Personalized Access to Scientific Publications: from Recommendation to Explanation. In: Carberry S., Weibelzahl S., Micarelli A., Semeraro G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg

Abstract

Several recommender systems have been proposed in the literature for adaptively suggesting useful references to researchers with different interests. However, in order to access the knowledge contained in the recommended papers, the users need to read the publications for identifying the potentially interesting concepts. In this work we propose to overcome this limitation by utilizing a more semantic approach where concepts are extracted from the papers for generating and explaining the recommendations. By showing the concepts used to find the recommended articles, users can have a preliminary idea about the filtered publications, can understand the reasons why the papers were suggested and they can also provide new feedback about the relevance of the concepts utilized for generating the recommendations.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Dario De Nart
    • 1
  • Felice Ferrara
    • 1
  • Carlo Tasso
    • 1
  1. 1.Artificial Intelligence Lab, Department of Mathematics and Computer ScienceUniversity of UdineItaly

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