Analyzing Museum Visitors' Behavior Patterns

  • Authors:

  • Massimo Zancanaro;Tsvi Kuflik;Zvi Boger;Dina Goren-Bar;Dan Goldwasser

  • Affiliations:

  • ITC-irst, via Sommarive 18, 38050 Povo, Italy;The University of Haifa, Mount Carmel, Haifa, 31905, Israel;Ben-Gurion University of the Negev, Beer Sheva,84105, Israel and OPTIMAL --- Industrial Neural Systems, Be'er Sheva 84243, Israel;The University of Haifa, Mount Carmel, Haifa, 31905, Israel;The University of Haifa, Mount Carmel, Haifa, 31905, Israel

  • Venue:
  • UM '07 Proceedings of the 11th international conference on User Modeling
  • Year:
  • 2007

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Abstract

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.