Abstract / Description of output
How will a content-based recommender system be perceived by museum visitors? How will it transform visitor experience, and how can we adapt recommender systems to meet the needs of users in the museum domain? In this paper, we demonstrate the implementation of a content-based recommender system to generate personalised museum tours within the UCL Grant Museum of Zoology, London, UK. We also outline pilot usability tests that were carried out to collect initial feedback on the system performance in the wild. The findings help detect critical issues before the system is tested with museum visitors to explore the potential transformation in visitor experience that occurs with content-based recommender systems in physical museums.
Original language | English |
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Title of host publication | Proceedings of the 1st International ‘Alan Turing’ Conference on Decision Support and Recommender Systems (DSRS-Turing 2019) |
Subtitle of host publication | The Alan Turing Institute, London, United Kingdom, 21-22nd November 2019 |
Editors | Iván Palomares |
Pages | 11-16 |
Number of pages | 6 |
ISBN (Electronic) | 9781526208200 |
Publication status | Published - 21 Nov 2019 |
Event | Proc. 1st International ‘Alan Turing’ Conference on Decision Support and Recommender Systems - The Alan Turing Institute, London, United Kingdom Duration: 21 Nov 2019 → 22 Nov 2019 https://dsrs-turing.github.io |
Conference
Conference | Proc. 1st International ‘Alan Turing’ Conference on Decision Support and Recommender Systems |
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Abbreviated title | (DSRS-Turing 2019) |
Country/Territory | United Kingdom |
City | London |
Period | 21/11/19 → 22/11/19 |
Internet address |