Improving Personalization and Contextualization of Queries to Knowledge Bases Using Spreading Activation and Users’ Feedback

  • Ana Belen Pelegrina
  • Maria J. Martin-Bautista
  • Pamela Faber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8502)


Facilitating knowledge acquisition when users are consulting knowledge bases (KB) is often a challenge, given the large amount of data contained. Providing users with appropriate contextualization and personalization of the content of KBs is a way to try to achieve this goal. This paper presents a mechanism intended to provide contextualization and personalization of queries to KBs based on collected data regarding users’ preferences, both implicitly (users’ profiles) and explicitly (users’ feedback). This mechanism combines user data with a spreading activation (SA) algorithm to generate the contextualization. The initial positive results of the evaluation of the contextualization are presented in this paper.


Knowledge base spreading activation user feedback contextualization personalization 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ana Belen Pelegrina
    • 1
  • Maria J. Martin-Bautista
    • 2
  • Pamela Faber
    • 1
  1. 1.Department of Translation and InterpretingUniversity of GranadaSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of GranadaSpain

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