A Group Recommender System for Tourist Activities

نویسندگان

  • Inma Garcia
  • Laura Sebastia
  • Eva Onaindia
  • Cesar Guzman
چکیده

Abstract. This paper introduces a method for giving recommendations of tourist activities to a group of users. This method makes recommendations based on the group tastes, their demographic classification and the places visited by the users in former trips. The group recommendation is computed from individual personal recommendations through the use of techniques such as aggregation, intersection or incremental intersection. This method is implemented as an extension of the e-Tourism tool, which is a user-adapted tourism and leisure application, whose main component is the Generalist Recommender System Kernel (GRSK), a domain-independent taxonomy-driven search engine that manages the group recommendation.

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تاریخ انتشار 2009