Personalized and content adaptive cultural heritage path recommendation: an application to the Gournia and Çatalhöyük archaeological sites

  • Georgios AlexandridisEmail author
  • Angeliki Chrysanthi
  • George E. Tsekouras
  • George Caridakis


Although abundant research work has been published in the area of path recommendation and its applications on travel and routing topics, scarce work has been reported on context-aware route recommendation systems aimed to stimulate optimal cultural heritage experiences. This paper tries to address this issue, by proposing a personalized and content adaptive cultural heritage path recommendation system, where location is modeled using mean-shift clustering trained with actual user movement patters. Additionally, topic modeling is incorporated to formalize the implicit cultural heritage content, while first order Markov models address the movement as a temporal transition aspect of the problem. The overall architecture is applied on data collected from actual visits to the archaeological sites of Gournia and Çatalhöyük and extensive analysis on visitor movement patterns follows, especially in comparison to the curated paths in the aforementioned sites. Finally, the offline evaluation results of the proposed recommendation scheme are encouraging, validating its efficiency and setting a positive paradigm for cultural heritage route recommendations.


Digital cultural heritage Personalized Cultural User eXperience Cultural heritage path recommendation Route recommendation Computer assisted archaeology User modeling 



We would like to thank Prof. Ian Hodder, director of the Çatalhöyük Research Project, as well as the Ephorate of Antiquities at Lasithi, Greek Ministry of Culture, for the permission to conduct the visitor survey at the archaeological sites of Çatalhöyük and Gournia respectively.


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Authors and Affiliations

  1. 1.Intelligent Interaction Research Group, Department of Cultural Technology and CommunicationUniversity of the AegeanMytileneGreece
  2. 2.Artificial Intelligence and Learning Systems Laboratory, School of Electrical and Computer EngineeringNational Technical University of AthensAthensGreece
  3. 3.Department of Cultural Technology and CommunicationUniversity of the AegeanMytileneGreece

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