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Title:On the role of dwell time for implicitly profiling museum visitors
Authors:ID Ferrato, Alessio (Author)
ID Sansonetti, Giuseppe (Author)
ID Tkalčič, Marko (Author)
Files:.pdf RAZ_Ferrato_Alessio_2026.pdf (672,97 KB)
MD5: 75339E29F8BC854487508373F19F53A6
 
URL https://dl.acm.org/doi/10.1145/3774935.3806782
 
Language:English
Work type:Unknown
Typology:1.08 - Published Scientific Conference Contribution
Organization:FAMNIT - Faculty of Mathematics, Science and Information Technologies
Abstract:How long visitors spend viewing artworks, often referred to as dwell time, has long been studied in museology as a potential behavioral indicator of engagement. However, dwell time may encode both genuine preference and situational factors such as fatigue, and disentangling these signals for computational modeling has received limited attention. This study investigates whether dwell time can serve as a valid preference indicator for implicit user modeling and whether incorporating it can improve artwork recommendation. Using the BIRD dataset, which includes eye-tracking data for extracting dwell times and explicit preferences from 51 museum visitors, we report three main findings. First, visitors spend significantly longer (9.27 seconds on average) viewing artworks they like, with a large effect size (Cohen’s d = 1.47). Second, we confirm the museum fatigue phenomenon, the progressive decline in visitor attention throughout a visit, observing a 34% reduction in dwell time from visit start to end. Third, we evaluate collaborative filtering approaches and find that while purely implicit models using dwell time alone perform near-chance level, a hybrid approach that uses dwell time to compute item similarities while predicting preferences from explicit likes achieves the best performance (AUC-ROC = 0.755, AP = 0.522). These findings suggest that dwell time provides complementary information to explicit feedback and can enhance museum recommendation systems when appropriately integrated.
Keywords:implicit, user modeling, recommender systems, artwork, museum
Publication version:Version of Record
Publication date:07.06.2026
Year of publishing:2026
Number of pages:Str. 413-417
PID:20.500.12556/RUP-23142 This link opens in a new window
UDC:004.8
DOI:10.1145/3774935.3806782 This link opens in a new window
COBISS.SI-ID:281036291 This link opens in a new window
Publication date in RUP:09.06.2026
Views:114
Downloads:6
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Record is a part of a monograph

Title:UMAP 2026 : proceedings of the 34th ACM International Conference on User Modeling, Adaptation and Personalization
Place of publishing:New York (NY)
Publisher:Association for Computing Machinery
ISBN:979-8-4007-2311-7
COBISS.SI-ID:280614403 This link opens in a new window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:N2-0354-2024
Name:Določanje uporabniške izkušnje z računalniškim psihološkim modeliranjem

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0465-2026
Name:Kognitivno računalništvo

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

Language:Slovenian
Abstract:Čas, ki ga obiskovalci porabijo za ogled umetniških del, pogosto imenovan čas zadrževanja (dwell time), je v muzeologiji že dolgo predmet raziskav kot možen vedenjski pokazatelj vključenosti obiskovalcev. Vendar pa lahko čas zadrževanja odraža tako resnične preference kot tudi situacijske dejavnike, kot je utrujenost, pri čemer je bilo razločevanju teh signalov za potrebe računalniškega modeliranja namenjene razmeroma malo pozornosti. Ta študija raziskuje, ali lahko čas zadrževanja služi kot veljaven pokazatelj preferenc za implicitno modeliranje uporabnikov in ali lahko njegova vključitev izboljša priporočanje umetniških del. Z uporabo podatkovne zbirke BIRD, ki vsebuje podatke o sledenju očem za pridobivanje časa zadrževanja ter eksplicitnih preferenc 51 muzejskih obiskovalcev, poročamo o treh glavnih ugotovitvah. Prvič, obiskovalci porabijo statistično značilno več časa za ogled umetniških del, ki so jim všeč (v povprečju 9,27 sekunde), pri čemer je učinek velik (Cohenov d = 1,47). Drugič, potrdimo pojav muzejske utrujenosti, to je postopnega upadanja pozornosti obiskovalcev med obiskom muzeja, saj opažamo 34-odstotno zmanjšanje časa zadrževanja od začetka do konca obiska. Tretjič, ovrednotimo pristope kolaborativnega filtriranja in ugotovimo, da modeli, ki temeljijo zgolj na implicitnih podatkih in uporabljajo samo čas zadrževanja, dosegajo rezultate blizu ravni naključnega ugibanja. Nasprotno pa hibridni pristop, ki uporablja čas zadrževanja za izračun podobnosti med umetniškimi deli, preference pa napoveduje na podlagi eksplicitno izraženih všečkov, dosega najboljšo uspešnost (AUC-ROC = 0,755; AP = 0,522). Te ugotovitve kažejo, da čas zadrževanja zagotavlja dopolnilne informacije k eksplicitnim povratnim informacijam ter lahko izboljša muzejske priporočilne sisteme, kadar je ustrezno vključen v model.
Keywords:implicitno, uporabniško modeliranje, priporočilni sistemi, umetnost, muzej


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