A museum visitors classification based on behavioral and demographic features

Moayad Mokatren; Alan Wecker; Veronika Bogina; Tsvi Kuflik

doi:10.1145/3314183.3323864

A museum visitors classification based on behavioral and demographic features

Moayad Mokatren, Alan Wecker, Veronika Bogina, Tsvi Kuflik

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper describes an exploratory study that attempts to classify museum visitors by taking into consideration indoor behavior and demographic features. We discuss different approaches of using such data for improving the user experience in the museum. Moreover, we try to explain user's behavior by creating different user groups using a novel data set. Our findings indicate that knowing user age, education and her museum visits frequency, together with the current visit signals (total standing time and listening to a mobile guide time) can be used for visitors classification that might be useful in designing new intelligent user interfaces that can improve the visitor's indoor experience.

Original language	English
Title of host publication	ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization
Publisher	Association for Computing Machinery, Inc
Pages	383-386
Number of pages	4
ISBN (Electronic)	9781450367110
DOIs	https://doi.org/10.1145/3314183.3323864
State	Published - 6 Jun 2019
Event	27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019 - Larnaca, Cyprus Duration: 9 Jun 2019 → 12 Jun 2019

Publication series

Name	ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization

Conference

Conference	27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019
Country/Territory	Cyprus
City	Larnaca
Period	9/06/19 → 12/06/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

Clustering
Cultural Heritage
Museum Interactions
User Modeling

ASJC Scopus subject areas

Software

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3314183.3323864

Cite this

Mokatren, M., Wecker, A., Bogina, V., & Kuflik, T. (2019). A museum visitors classification based on behavioral and demographic features. In ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization (pp. 383-386). (ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization). Association for Computing Machinery, Inc. https://doi.org/10.1145/3314183.3323864

Mokatren, Moayad ; Wecker, Alan ; Bogina, Veronika et al. / A museum visitors classification based on behavioral and demographic features. ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2019. pp. 383-386 (ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization).

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title = "A museum visitors classification based on behavioral and demographic features",

abstract = "This paper describes an exploratory study that attempts to classify museum visitors by taking into consideration indoor behavior and demographic features. We discuss different approaches of using such data for improving the user experience in the museum. Moreover, we try to explain user's behavior by creating different user groups using a novel data set. Our findings indicate that knowing user age, education and her museum visits frequency, together with the current visit signals (total standing time and listening to a mobile guide time) can be used for visitors classification that might be useful in designing new intelligent user interfaces that can improve the visitor's indoor experience.",

keywords = "Clustering, Cultural Heritage, Museum Interactions, User Modeling",

author = "Moayad Mokatren and Alan Wecker and Veronika Bogina and Tsvi Kuflik",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019 ; Conference date: 09-06-2019 Through 12-06-2019",

year = "2019",

month = jun,

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doi = "10.1145/3314183.3323864",

language = "English",

series = "ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization",

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Mokatren, M , Wecker, A, Bogina, V & Kuflik, T 2019, A museum visitors classification based on behavioral and demographic features. in ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, Inc, pp. 383-386, 27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019, Larnaca, Cyprus, 9/06/19. https://doi.org/10.1145/3314183.3323864

A museum visitors classification based on behavioral and demographic features. / Mokatren, Moayad ; Wecker, Alan; Bogina, Veronika et al.
ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2019. p. 383-386 (ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A museum visitors classification based on behavioral and demographic features

AU - Mokatren, Moayad

AU - Wecker, Alan

AU - Bogina, Veronika

AU - Kuflik, Tsvi

PY - 2019/6/6

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N2 - This paper describes an exploratory study that attempts to classify museum visitors by taking into consideration indoor behavior and demographic features. We discuss different approaches of using such data for improving the user experience in the museum. Moreover, we try to explain user's behavior by creating different user groups using a novel data set. Our findings indicate that knowing user age, education and her museum visits frequency, together with the current visit signals (total standing time and listening to a mobile guide time) can be used for visitors classification that might be useful in designing new intelligent user interfaces that can improve the visitor's indoor experience.

AB - This paper describes an exploratory study that attempts to classify museum visitors by taking into consideration indoor behavior and demographic features. We discuss different approaches of using such data for improving the user experience in the museum. Moreover, we try to explain user's behavior by creating different user groups using a novel data set. Our findings indicate that knowing user age, education and her museum visits frequency, together with the current visit signals (total standing time and listening to a mobile guide time) can be used for visitors classification that might be useful in designing new intelligent user interfaces that can improve the visitor's indoor experience.

KW - Clustering

KW - Cultural Heritage

KW - Museum Interactions

KW - User Modeling

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U2 - 10.1145/3314183.3323864

DO - 10.1145/3314183.3323864

M3 - Conference contribution

AN - SCOPUS:85068671291

T3 - ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization

SP - 383

EP - 386

BT - ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization

PB - Association for Computing Machinery, Inc

T2 - 27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019

Y2 - 9 June 2019 through 12 June 2019

ER -

Mokatren M , Wecker A, Bogina V, Kuflik T. A museum visitors classification based on behavioral and demographic features. In ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc. 2019. p. 383-386. (ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization). doi: 10.1145/3314183.3323864

A museum visitors classification based on behavioral and demographic features

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this