Analyzing museum visitors' behavior patterns

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationUser Modeling 2007 - 11th International Conference, UM 2007, Proceedings
PublisherSpringer Verlag
Pages238-246
Number of pages9
ISBN (Print)9783540730774
DOIs
StatePublished - 2007
Event11th International on User Modeling Conference, UM 2007 - Corfu, Greece
Duration: 25 Jun 200729 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International on User Modeling Conference, UM 2007
Country/TerritoryGreece
CityCorfu
Period25/06/0729/06/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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