Analysis and prediction of museum visitors' behavioral pattern types

Tsvi Kuflik, Zvi Boger, Massimo Zancanaro

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Personalization in the "museum visit" scenario is extremely challenging, especially since in many cases visitors come to the museum for the first time, and it may be the last time in their life. There is therefore a need to generate an effective user model quickly without any prior knowledge. Furthermore, the initial definition of a user model is also challenging since it should be built in a non-intrusive manner. Understanding visitors' behavioral patterns may help in initializing their user models and supporting them better. This chapter reports three stages of analysis of behavior patterns of museum visitors. The first step assesses, following past ethnographic research, whether a distinct stereotype of behavior can be identified; the second shows that visitors' behavior is not always consistent; the third shows that, in spite of the inconsistency, prediction of visitor type, is possible.

Original languageAmerican English
Title of host publicationUbiquitous Display Environments
EditorsAntonio Kruger, Tsvi Kuflik
Number of pages16
StatePublished - 2012

Publication series

NameCognitive Technologies

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence


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