Analysis of visitors’ mobility patterns through random walk in the Louvre Museum

This paper proposes a random walk model to analyze visitors' mobility patterns in a large museum. Visitors' available time makes their visiting styles different, resulting in dissimilarity in the order and number of visited places and in path sequence length. We analyze all this by comparing a simulation model and observed data, which provide us the strength of the visitors' mobility patterns. The obtained results indicate that shorter stay-type visitors exhibit stronger patterns than those with the longer stay-type, confirming that the former are more selective than the latter in terms of their visitation type.Comment: 16 pages, 5 figures, 4 table

Mappe media citt\ue0. Territorializzazioni e orizzonti di progetto nell'epoca dei Big Data

La ricerca identifica la relazione tra nuovi sistemi di comunicazione e strategie di progetto analizzando le implicazioni per la pratica progettuale attraverso le diverse categorie di controllo dei dispositivi spaziali che oggi vengono utilizzati per la mappatura dei territori. L\u2019attenzione \ue8 rivolta alla mappatura dei luoghi soggetti a fenomeni emergenziali come terremoti e alluvioni. L\u2019oggetto della ricerca sono quindi le citt\ue0 mutevoli: sistemi colpiti da fenomeni calamitosi, come dissesto causato dall\u2019attivit\ue0 fluviale e torrentizia, che hanno caratteristiche estremamente variabili e danno luogo a processi complessi, i cui parametri non sempre risultano facilmente individuabili. L\u2019analisi dell\u2019evoluzione spazio-temporale degli eventi e dei loro effetti, pu\uf2 essere studiata attraverso l\u2019utilizzo di un sistema informativo integrato che riconsideri le forme di mappatura e di analisi del territorio e che riporti l\u2019esperienza umana degli eventi, la simbolizzazione dei luoghi e la leggibilit\ue0 del territorio, fruibile non solo da parte degli specialisti ma anche dei cittadini. Una redazione cartografica real-time, che permetta un legame stretto tra le tecnologie satellitari di monitoraggio e la condivisione di esperienze dei luoghi abitati attraverso i nuovi mezzi di comunicazione, apre ai cittadini la possibilit\ue0 di partecipare alla redazione della cartografia di progetto

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

[EN] The study presents some results of customer paths¿ analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men¿s bathroom or women¿s bathroom. Since the study has a comprehensive scope, we focused on male and female customers¿ behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.Dogan, O.; Bayo-Monton, JL.; Fernández Llatas, C.; Oztaysi, B. (2019). Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application. Sensors. 19(3):1-20. https://doi.org/10.3390/s19030557S120193Oosterlinck, D., Benoit, D. F., Baecke, P., & Van de Weghe, N. (2017). Bluetooth tracking of humans in an indoor environment: An application to shopping mall visits. Applied Geography, 78, 55-65. doi:10.1016/j.apgeog.2016.11.005Merad, D., Aziz, K.-E., Iguernaissi, R., Fertil, B., & Drap, P. (2016). Tracking multiple persons under partial and global occlusions: Application to customers’ behavior analysis. Pattern Recognition Letters, 81, 11-20. doi:10.1016/j.patrec.2016.04.011Wu, Y., Wang, H.-C., Chang, L.-C., & Chou, S.-C. (2015). 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An Analysis of Visitors’ Behavior in the Louvre Museum: A Study Using Bluetooth Data. Environment and Planning B: Planning and Design, 41(6), 1113-1131. doi:10.1068/b130047pDe Leoni, M., van der Aalst, W. M. P., & Dees, M. (2016). A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs. Information Systems, 56, 235-257. doi:10.1016/j.is.2015.07.003Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Arroyo, R., Yebes, J. J., Bergasa, L. M., Daza, I. G., & Almazán, J. (2015). Expert video-surveillance system for real-time detection of suspicious behaviors in shopping malls. Expert Systems with Applications, 42(21), 7991-8005. doi:10.1016/j.eswa.2015.06.016Popa, M. C., Rothkrantz, L. J. M., Shan, C., Gritti, T., & Wiggers, P. (2013). Semantic assessment of shopping behavior using trajectories, shopping related actions, and context information. Pattern Recognition Letters, 34(7), 809-819. doi:10.1016/j.patrec.2012.04.015Kang, L., & Hansen, M. (2017). Behavioral analysis of airline scheduled block time adjustment. Transportation Research Part E: Logistics and Transportation Review, 103, 56-68. doi:10.1016/j.tre.2017.04.004Rovani, M., Maggi, F. M., de Leoni, M., & van der Aalst, W. M. P. (2015). Declarative process mining in healthcare. Expert Systems with Applications, 42(23), 9236-9251. doi:10.1016/j.eswa.2015.07.040Fernández-Llatas, C., Benedi, J.-M., García-Gómez, J., & Traver, V. (2013). Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes. Sensors, 13(11), 15434-15451. doi:10.3390/s131115434Van der Aalst, W. M. P., Reijers, H. A., Weijters, A. J. M. M., van Dongen, B. F., Alves de Medeiros, A. K., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732. doi:10.1016/j.is.2006.05.003M. Valle, A., A.P. Santos, E., & R. Loures, E. (2017). Applying process mining techniques in software process appraisals. Information and Software Technology, 87, 19-31. doi:10.1016/j.infsof.2017.01.004Juhaňák, L., Zounek, J., & Rohlíková, L. (2019). Using process mining to analyze students’ quiz-taking behavior patterns in a learning management system. Computers in Human Behavior, 92, 496-506. doi:10.1016/j.chb.2017.12.015Sedrakyan, G., De Weerdt, J., & Snoeck, M. (2016). Process-mining enabled feedback: «Tell me what I did wrong» vs. «tell me how to do it right». Computers in Human Behavior, 57, 352-376. doi:10.1016/j.chb.2015.12.040Schoor, C., & Bannert, M. (2012). Exploring regulatory processes during a computer-supported collaborative learning task using process mining. 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Better museum maps: an empirical study comparing the appeal and effectiveness of graphic design approaches

Visitor maps are a key resource that many people use to facilitate their visit to a museum. This thesis sets out to understand how such maps are used by visitors, to investigate the range of graphic design approaches and elements that are employed in their design, and to consider how map design can improve museum visitors’ experiences. The research examines the range of information different maps attempt to convey, and the graphic means they use to do it, using of a corpus of around 250 contemporary museum maps from around the world. A historical perspective is also gained through an examination of the design of maps produced by two major UK museums throughout their history. Three linked surveys of museum visitors investigating the use of maps and digital guides reveal that, when using maps, while people are interested in navigation, their prime interest is what the museum holds. These surveys also reveal that, at a time of high digital device ownership and use, many museum visitors still favour printed maps over digital guide devices. Two empirical studies examine particular aspects of map design: the relative effectiveness and appeal of two-dimensional or three-dimensional depictions; and the appeal of two methods for labelling exhibition spaces (location labels on the map, and a directory-style list). The first study suggests that three-dimensional representations can better help people understand the layout of a museum, as they can more clearly show the building as a whole, and the ways of moving between floors. However, threedimensional representations can, in themselves, create complexity that make maps difficult for some users to use. The second study suggests that using a directory labelling system may mitigate this sense of complexity. This research provides insights into how museum visitors use maps, and particular issues in the design of maps that can impede their understanding of the museum’s layout, which can help map designers. The thesis concludes by identifying avenues for further research that would improve our understanding of design features that best serve museum visitors with varying needs and mapreading abilities

Human and Artificial Intelligence

Although tremendous advances have been made in recent years, many real-world problems still cannot be solved by machines alone. Hence, the integration between Human Intelligence and Artificial Intelligence is needed. However, several challenges make this integration complex. The aim of this Special Issue was to provide a large and varied collection of high-level contributions presenting novel approaches and solutions to address the above issues. This Special Issue contains 14 papers (13 research papers and 1 review paper) that deal with various topics related to human–machine interactions and cooperation. Most of these works concern different aspects of recommender systems, which are among the most widespread decision support systems. The domains covered range from healthcare to movies and from biometrics to cultural heritage. However, there are also contributions on vocal assistants and smart interactive technologies. In summary, each paper included in this Special Issue represents a step towards a future with human–machine interactions and cooperation. We hope the readers enjoy reading these articles and may find inspiration for their research activities