TY - GEN
T1 - Analyzing museum visitors' behavior patterns
AU - Zancanaro, Massimo
AU - Kuflik, Tsvi
AU - Boger, Zvi
AU - Goren-Bar, Dina
AU - Goldwasser, Dan
PY - 2007
Y1 - 2007
N2 - Many studies have investigated personalized information presentation in the context of mobile museum guides. In order to provide such a service, information about museum visitors has to be collected and visitors have to be monitored and modelled in a non-intrusive manner. This can be done by using known museum visiting styles to classify the visiting style of visitors as they start their visit. Past research applied ethnographic observations of the behaviour of visitors and qualitative analysis (mainly site studies and interviews with staff) in several museums to define visiting styles. The current work validates past ethnographic research by applying unsupervised learning approaches to visitors classification. By providing quantitative empirical evidence for a qualitative theory we claim that, from the point of view of assessing the suitability of a qualitative theory in a given scenario, this approach is as valid as a manual annotation of museum visiting styles.
AB - Many studies have investigated personalized information presentation in the context of mobile museum guides. In order to provide such a service, information about museum visitors has to be collected and visitors have to be monitored and modelled in a non-intrusive manner. This can be done by using known museum visiting styles to classify the visiting style of visitors as they start their visit. Past research applied ethnographic observations of the behaviour of visitors and qualitative analysis (mainly site studies and interviews with staff) in several museums to define visiting styles. The current work validates past ethnographic research by applying unsupervised learning approaches to visitors classification. By providing quantitative empirical evidence for a qualitative theory we claim that, from the point of view of assessing the suitability of a qualitative theory in a given scenario, this approach is as valid as a manual annotation of museum visiting styles.
UR - http://www.scopus.com/inward/record.url?scp=37249036020&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-73078-1_27
DO - 10.1007/978-3-540-73078-1_27
M3 - Conference contribution
AN - SCOPUS:37249036020
SN - 9783540730774
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 238
EP - 246
BT - User Modeling 2007 - 11th International Conference, UM 2007, Proceedings
PB - Springer Verlag
T2 - 11th International on User Modeling Conference, UM 2007
Y2 - 25 June 2007 through 29 June 2007
ER -