A Method of Designing Museum Ubiquitous Visitor Model
AUTHORS
Preeti Khanwalkar,Protocol Engineering and Technology Unit,Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, India
Pallapa Venkataram,Protocol Engineering and Technology Unit,Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, India
ABSTRACT
Museum ubiquitous visitors need personalized services according to their requirements. For providing personalized services to the museum’s ubiquitous visitors, this paper presents the museum Ubiquitous Visitor Model. The Museum Ubiquitous Visitor Model is designed by combining ubiquitous Visitor Personal Information (VPI), Essential Context-derived Reasons (ECR), and Interests of the ubiquitous visitors. For designing the museum Ubiquitous Visitor Model, the information about ubiquitous visitors is obtained both implicitly and explicitly. The context information of the museum’s ubiquitous visitors is collected implicitly and deduced into Essential Context-derived Reasons (ECR). The ubiquitous visitor’s Interest is obtained implicitly from his/her history of exhibit information museum services access. On the contrary, VPI is obtained explicitly through the pre-visit registration process. Museum Ubiquitous Visitor Model (UbiVM) as cases characterize the tuple of multifaceted information about ubiquitous visitors which enables the system to understand their requirements to provide personalized services. We conducted simulation with the available accuracy of ECR and the history of exhibit information museum service access. The simulation results show that the accuracy of the museum Ubiquitous Visitor Model increases with the increase in the accuracy of ECR and the available history of exhibit information museum service access of the ubiquitous visitors. The designed Ubiquitous Visitor Model also decreases the system resource usage and the number of requests to the museum exhibit information server.
KEYWORDS
Museum ubiquitous visitors, ECR, Interests, Ubiquitous visitor personal information, Museum ubiquitous visitor model
REFERENCES
[1] Fabian Bohnert and Ingrid Zukerman, “Personalized viewing-time prediction in museums,” In User Modeling and User-Adapted Interaction, vol.24, pp.263-314, (2014)
[2] Mikko Perttunen, Jukka Riekki, and Ora Lassila, “Context representation and reasoning in pervasive computing: a review,” In International Journal of Multimedia and Ubiquitous Engineering, vol.4, pp.1-28, (2009)
[3] G. Caridakis, G. Konstantakis, and M. Alexandridis, “A personalized heritage-oriented recommender system based on extended cultural tourist typologies,” In Big Data Cognitive Computing, vol.12, Apr., (2020)
[4] Tuukka Ruotsalo, Eetu M¨akel¨a, Tomi Kauppinen, Eero Hyv¨onen, Krister Haav, Ville Rantala, Matias Frosterus, Nima Dokoohaki, and Mihhail Matskin, “Smartmuseum: Personalized context-aware access to digital cultural heritage,” In Proceedings of the International Conferences on Digital Libraries and the Semantic Web ICSD, Sep., (2009)
[5] Pallapa Venkataram and M. Bharath, “A method of context-based services discovery in ubiquitous environment,” In Context-Aware Systems and Applications, Social Informatics and Telecommunications Engineering, Lecture Notes of the Institute for Computer Sciences, Springer International Publishing, vol.128, pp.260-270, (2014)
[6] YoungJe Yu and Woo June, “Educational effectiveness of virtual museum,” In International Journal of Multimedia and Ubiquitous Engineering, vol.13, pp.21-26, (2018)
[7] Preeti Khanwalkar and Pallapa Venkataram. “A weight based context analysis system to provide a required ubiquitous multimedia service,” In Proceedings of International Conference on Wireless Networks, pp.153-159, July., (2011)
[8] Yoondeuk Seo and Young-Eun, “An users viewing exhibit similarity-based contents recommendation service by activity recognition,” In International Journal of Multimedia and Ubiquitous Engineering, vol.8, pp.387-396, Nov., (2013)
[9] Byung-Eun Park and Dae-Geun Lim, “Recording process of visual archive for cultural heritage,” In International Journal of Multimedia and Ubiquitous Engineering, vol.8, pp.397-406, 11, (2013)
[10] Reza Khoshkangini, Giuseppe Valetto, A. Marconi, and Marco Pistore. “Automatic generation and recommendation of personalized challenges for gamification,” In User Modeling and User-Adapted Interaction, pp.1-34, (2020)
[11] Olivero Stock, Massimo Zancanaro, Paolo Busetta, Charles Callaway, Antonio Kr¨uger, Michael Kruppa, Tsvi Kuflik, Elena Not, and Cesare Rocchi, “Adaptive intelligent presentation of information for the museum visitor in peach,” In User Modeling and User-Adapted Interaction, vol.17, pp.257-304, July., (2007)
[12] Chianese, F. Marulli, V. Moscato, and F. Piccialli, “A smart multimedia guide for indoor contextual navigation in cultural heritage applications,” In International Conference on Indoor Positioning and Indoor Navigation, pp.1-6, Oct., (2013)
[13] S. Jung and S. Kim, “Augmented reality-based exhibit information personalized service architecture through spectator’s context analysis,” In International Journal of Multimedia and Ubiquitous Engineering, vol.8, pp.313-320, Jan., (2013)
[14] Preeti Khanwalkar and Pallapa Venkataram, “Organization of museum exhibit information for ubiquitous visitors,” In EAI Endorsed Transactions on Creative Technologies: Online First, Aug., (2020)
[15] Landy Rajaonarivo, Eric Maisel, and Pierre De Loor, “An evolving museum metaphor applied to cultural heritage for personalized content delivery,” Feb., (2019)
[16] David Walsh, Mark Hall, Paul Clough, and Jonathan Foster, “Characterising online museum users: A study of the national museums liverpool museum website,” In International Journal on Digital Libraries, July., (2020)
[17] Wahidah Husain and Lam Dih, “A framework of a personalized location-based traveler recommendation system in mobile application,” In International Journal of Multimedia and Ubiquitous Engineering, vol.7, July., (2012)
[18] Moneerah Almeshari, John Dowell, and Julianne Nyhan, “Using personas to model museum visitors,” In ACM Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization (UMAP), May., (2019)
[19] Ivo Roes, Natalia Stash, Yiwen Wang, and Lora Aroyno, “A personalized walk through the museum: The chip interactive tour guide,” In CHI, Extended Abstracts on Human Factors in Computing Systems, pp.3317-3322, (2009)
[20] M. Pechenizkiy and T. Calders, “A framework for guiding the museum tour personalization,” In Proceedings of the Workshop on Personalized Access to Cultural Heritage (PATCH), IIT, NCSR Demokritos, pp.11-28, (2007)
[21] Nikolaos Partarakis, Margherita Antona, Emmanouil Zidianakis, and Constantine Stephanidis, “Adaptation and content personalization in the context of multi user museum exhibits,” In AVI*CH, (2016)
[22] Shlomo Berkovsky, Tsvi Kuflik, and Francesco Ricci, “Mediation of user models for enhanced personalization in recommender systems,” In User Modeling and User-Adapted Interaction, vol.18, pp.245-286, Aug., (2008)
[23] Lloyd Rutledge, Lora Aroyo, and Natalia Stash. Determining user interests about museum collections. In ACM Proceedings of the 15th International Conference on World Wide Web, WWW, pp.855-856, (2006)
[24] Andreas Zimmermann and Andreas Lorenz, “Listen: a user-adaptive audio-augmented museum guide,” In User Modeling and User-Adapted Interaction, vol.18, pp.389-416, Nov., (2008)
[25] Tsvi Kuflik, Oliviero Stock, Massimo Zancanaro, Ariel Gorfinkel, Sadek Jbara, Shahar Kats, Julia Sheidin, and Nadav Kashtan, “A visitor’s guide in an active museum: Presentations, communications, and reflection,” In Journal on Computing and Cultural Heritage (JOCCH), vol.3, pp.11, Mar., (2011)
[26] Tsvi Kuflik, Judy Kay, and Bob Kummerfeld, “Lifelong personalized museum experiences,” In Pervasive User Modeling and Personalization (PUMP), Workshop User Modeling, Adaptation and Personalization, pp.9-16, June., (2018)
[27] Fabian Bohnert, Ingrid Zukerman, Shlomo Berkovsky, Timothy Baldwin, and Liz Sonenberg, “Using interest and transition models to predict visitor locations in museums,” In AI Communications - Recommender Systems, IOS Press, vol.21, pp.195-202, Apr., (2008)
[28] Liliana Ardissono, Tsvi Kuflik, and Daniela Petrelli, “Personalization in cultural heritage: The road traveled and the one ahead,” In User Modeling and User-Adapted Interaction, Kluwer Academic Publishers, vol.22, pp.73-99, (2012)
[29] Tsvi Kuflik, Judy Kay, and Bob Kummerfeld, “Challenges and solutions of ubiquitous user modeling,” In Ubiquitous Display Environments, pp.7-30, (2012)
[30] Angeliki Antoniou and George Lepouras, “Modeling visitors’ profiles: A study to investigate adaptation aspects for museum learning technologies,” In Journal on Computing and Cultural Heritage, ACM, vol.3, pp.7:1-7:19, Oct., (2010)
[31] Dimitrios Kosmopoulos and Georgios Styliaras, “A survey on developing personalized content services in museums,” In Pervasive and Mobile Computing, vol.47, pp.54-77, (2018).
[32] Daniel Wessel and Eva Mayr. Potentials and challenges of mobile media in museums. In International Journal of Interactive Mobile Technologies (iJIM), vol.1, Oct., (2007)
[33] Reinhard Oppermann and Marcus Specht, “A context-sensitive nomadic exhibition guide,” In Handheld and Ubiquitous Computing (HUC), Springer Berlin Heidelberg, pp.127-142, (2000)
[34] Fabian Bohnert, Ingrid Zukerman, and Junaidy Laures, “Geckommender: Personalized theme and tour recommendations for museums,” In International Conference on User Modeling, Adaptation, and Personalization, Springer, vol.7379, pp.26-37, July., (2012)
[35] Andry Rakotonirainy and Nicholas Lehman, “Augmenting a museum visitor’s tour with a context aware framework,” In 1st International Workshop on Ubiquitous Computing, INSTICC Press, pp.104-112, (2004)
[36] Shlomo Berkovsky, Timothy Baldwin, and Ingrid Zukerman, “Aspect-based personalized text summarization,” In Adaptive Hypermedia and Adaptive Web-Based Systems, Springer Berlin Heidelberg, pp.267-270, July., (2008)
[37] Andrew D. Bagdanov, Alberto Del Bimbo, Lea Landucci, and Federico Pernici, “Mnemosyne: Enhancing the museum experience through interactive media and visual profiling,” In Communications in Computer and Information Science, vol.247, pp.38-50, Jan., (2012)
[38] Marek Hatala and RonWakkary, “Ontology-based user modeling in an augmented audio reality system for museums,” In User Modeling and User-Adapted Interaction, vol.15, pp.339-380, Aug., (2005)
[39] Adrian Bright, Judy Kay, Daren Ler, Kelvin Ngo, William Niu, and Alfonse Nuguid, “Adaptively recommending museum tours,” In Proceedings: Workshop on Smart Environments and Their Applications to Cultural Heritage at UbiComp, pp.29-32, (2005)
[40] Bouidghaghen and L Tamine, “Spatio-temporal based personalization for mobile search,” In Next Generation Search Engines: Advanced Models for Information Retrieval, pp.386-409, Jan., (2012)
[41] Angeliki Antoniou, Akrivi Katifori, Maria Roussou, Maria Vayanou, Manolis Karvounis, Marialena Kyriakidi, and Laia Pujol-Tost, “Capturing the visitor profile for a personalized mobile museum experience: an indirect approach,” In 24th ACM Conference on User Modeling, Adaptation and Personalisation(UMAP), Workshop on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE), (2016)
[42] Preeti Khanwalkar and Pallapa Venkataram, “Context-based service identification in the museum environment,” In Proceedings of the 4th EAI International Conference on Context-Aware Systems and Applications, ICCASA, Springer International Publishing, pp.151-164, (2016)
[43] Preeti Khanwalkar and Pallapa Venkataram, “Essential context-derived reasons formation from context information of museum ubiquitous visitors,” In EAI Endorsed Transactions on Context-aware Systems and Applications(CASA): Online First, Aug., (2020)
[44] Juan Brida, Marta Disegna, and Raffaele Scuderi, “The behavior of repeat visitors to museums: review and empirical findings,” In Quality and Quantity: International Journal of Methodology, vol.48, pp.2817-2840, Sep., (2014)
[45] Juan Gabriel Brida, Marta Meleddu, and Manuela Pulina, “Factors influencing the intention to revisit a cultural attraction: The case study of the museum of modern and contemporary art in roveretno,” In Journal of Cultural Heritage, vol.13, Jan., (2011)
[46] Melbourne Museum Dataset. https://umlt.infotech.monash.edu/?page id=140.
[47] Fabian Bohnert and Ingrid Zukerma, “Personalised viewing-time prediction in museums,” In User Modeling and User-Adapted Interaction, vol.24, pp.263-314, Oct., (2014)
[48] B. Bonis, J. Stamos, S. Vosinakis, I. Andreou, and T. Panayiotopoulos, “A platform for virtual museums with personalized content,” In Multimedia Tools and Applications, vol.42, pp.139-159, Apr., (2009)
[49] D.A. Adeniyi, Z. Wei, and Y. Yongquan, “Automated web usage data mining and recommendation system using k-nearest neighbor (knn) classification method,” In Applied Computing and Informatics, vol.12, pp.90 - 108, (2016)
[50] Tsvi Kuflik, Alan J. Wecker, Joel Lanir, and Oliviero Stock, “An integrative framework for extending the boundaries of the museum visit experience: linking the pre, during and post visit phases,” In Information Technology and Tourism, vol.15, pp.17-47, (2015)
[51] Alfred Kobsa, “Generic user modeling systems,” In User Modeling and User-Adapted Interaction, vol.11, pp.49-63, Mar., (2001)