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SculptMate: Personalizing cultural heritage experience using fuzzy weights

Published:16 June 2023Publication History

ABSTRACT

Virtual Environment (VE) technology has become increasingly popular in the cultural heritage field, providing new ways to experience and interact with cultural artifacts and sites. By creating immersive and realistic virtual environments, VE technology allows users to explore and engage with cultural heritage in a more dynamic and engaging way. Towards this direction, this study introduces SculptMate, a cutting-edge mobile application that uses advanced personalization features (fuzzy logic) to enhance the appreciation and understanding of sculptures from various eras and artistic styles. The application aims to provide users with an immersive and interactive experience, both within and beyond museum settings, by allowing them to explore and interact with an extensive collection of virtual sculptures from museums and galleries worldwide. The paper's objectives are to investigate the potential of SculptMate, examine the effectiveness of fuzzy logic in personalizing the user experience, and assess the impact of the personalized experience on user engagement and satisfaction. The novelty of this study lies in the utilization of fuzzy logic in VE for personalizing the cultural heritage experience. SculptMate has been evaluated with very promising results.

References

  1. C. B. M. Van Riel, “Why do people love museums so much? Empirical evidence about the stellar reputations of art museums and what companies can learn from it,” Research in Global Strategic Management, vol. 18, pp. 185–209, 2019, doi: 10.1108/S1064-485720190000018013/FULL/EPUB.Google ScholarGoogle ScholarCross RefCross Ref
  2. N. Partarakis, M. Antona, E. Zidianakis, and C. Stephanidis, “Adaptation and Content Personalization in the Context of Multi User Museum Exhibits,” 2016.Google ScholarGoogle Scholar
  3. E. Ch'Ng, Y. Li, S. Cai, and F. T. Leow, “The effects of VR environments on the acceptance, experience, and expectations of cultural heritage learning,” Journal on Computing and Cultural Heritage, vol. 13, no. 1, Feb. 2020, doi: 10.1145/3352933.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Grammatikopoulou and N. Grammalidis, “Artful—An AR Social Self-Guided Tour App for Cultural Learning in Museum Settings,” Information, vol. 14, no. 3, p. 158, Mar. 2023, doi: 10.3390/INFO14030158.Google ScholarGoogle ScholarCross RefCross Ref
  5. J. Keil ., “A digital look at physical museum exhibits: Designing personalized stories with handheld Augmented Reality in museums,” Proceedings of the DigitalHeritage 2013 - Federating the 19th Int'l VSMM, 10th Eurographics GCH, and 2nd UNESCO Memory of the World Conferences, Plus Special Sessions fromCAA, Arqueologica 2.0 , vol. 2, pp. 685–688, 2013, doi: 10.1109/DIGITALHERITAGE.2013.6744836.Google ScholarGoogle ScholarCross RefCross Ref
  6. M. Skamantzari and A. Georgopoulos, “3D Visualization for virtual museum development,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. 41, pp. 961–968, 2016, doi: 10.5194/ISPRSARCHIVES-XLI-B5-961-2016.Google ScholarGoogle Scholar
  7. C. Kiourt, A. Koutsoudis, F. Arnaoutoglou, G. Petsa, S. Markantonatou, and G. Pavlidis, “A dynamic web-based 3D virtual museum framework based on open data,” 2015 Digital Heritage International Congress, Digital Heritage 2015, pp. 647–650, 2015, doi: 10.1109/DIGITALHERITAGE.2015.7419589.Google ScholarGoogle ScholarCross RefCross Ref
  8. F. Kong and F. Kong, “Application of Artificial Intelligence in Modern Art Teaching,” International Journal of Emerging Technologies in Learning (iJET), vol. 15, no. 13, pp. 238–251, 2020.Google ScholarGoogle ScholarCross RefCross Ref
  9. K. Choromański , “Development of Virtual Reality Application for Cultural Heritage Visualization from Multi-Source 3d Data,” ISPAr, vol. 42W9, no. 2/W9, pp. 261–267, Jan. 2019, doi: 10.5194/ISPRS-ARCHIVES-XLII-2-W9-261-2019.Google ScholarGoogle Scholar
  10. Q. Hu, D. Yu, S. Wang, C. Fu, M. Ai, and W. Wang, “Hybrid three-dimensional representation based on panoramic images and three-dimensional models for a virtual museum: Data collection, model, and visualization,” Inf Vis, vol. 16, no. 2, pp. 126–138, Apr. 2017, doi: 10.1177/1473871616655467/ASSET/IMAGES/LARGE/10.1177_1473871616655467-FIG14.JPEG.Google ScholarGoogle ScholarCross RefCross Ref
  11. J. Xiao and Y. Furukawa, “Reconstructing the World's Museums,” Int J Comput Vis, vol. 110, no. 3, pp. 243–258, Dec. 2014, doi: 10.1007/S11263-014-0711-Y.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. E. Zidianakis , “The Invisible Museum: A User-Centric Platform for Creating Virtual 3D Exhibitions with VR Support,” Electronics 2021, Vol. 10, Page 363, vol. 10, no. 3, p. 363, Feb. 2021, doi: 10.3390/ELECTRONICS10030363.Google ScholarGoogle Scholar
  13. D. A. Loaiza Carvajal, M. M. Morita, and G. M. Bilmes, “Virtual museums. Captured reality and 3D modeling,” J Cult Herit, vol. 45, pp. 234–239, Sep. 2020, doi: 10.1016/J.CULHER.2020.04.013.Google ScholarGoogle ScholarCross RefCross Ref
  14. M. B. Carmo and A. P. Cláudio, “3D virtual exhibitions,” DESIDOC Journal of Library and Information Technology, vol. 33, no. 3, pp. 222–235, 2013, doi: 10.14429/DJLIT.33.3.4608.Google ScholarGoogle ScholarCross RefCross Ref
  15. E. Not and D. Petrelli, “Balancing adaptivity and customisation: In search of sustainable personalisation in cultural heritage,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8538, pp. 405–410, 2014, doi: 10.1007/978-3-319-08786-3_36.Google ScholarGoogle Scholar
  16. H. Lee, T. H. Jung, M. C. tom Dieck, and N. Chung, “Experiencing immersive virtual reality in museums,” Information & Management, vol. 57, no. 5, p. 103229, Jul. 2020, doi: 10.1016/J.IM.2019.103229.Google ScholarGoogle ScholarCross RefCross Ref
  17. C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Modeling the Knowledge of Users in an Augmented Reality-Based Learning Environment Using Fuzzy Logic,” Lecture Notes in Networks and Systems, vol. 556 LNNS, pp. 113–123, 2023, doi: 10.1007/978-3-031-17601-2_12.Google ScholarGoogle Scholar
  18. C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, “Personalization of the Learning Path within an Augmented Reality Spatial Ability Training Application Based on Fuzzy Weights,” Sensors 2022, Vol. 22, Page 7059, vol. 22, no. 18, p. 7059, Sep. 2022, doi: 10.3390/S22187059.Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Conferences
    UMAP '23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    June 2023
    446 pages
    ISBN:9781450398916
    DOI:10.1145/3563359

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    • Published: 16 June 2023

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