Modelling and predicting movements of museum visitors: A simulation framework for assessing the impact of sensor noise on model performance

Fabian Bohnert, Ingrid Zukerman, David William Albrecht, Timothy Baldwin

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    Abstract

    We present a simulation framework to examine the impact of sensor noise on the performance of user models in the museum domain. Our contributions are: (1) models to simulate noisy visit trajectories as time-stamped sequences of (x, y) positional coordinates which reflect walking and hovering behaviour; (2) a discriminative inference model that distinguishes between hovering and walking on the basis of (simulated) noisy sensor observations; (3) a model that infers viewed exhibits from hovering coordinates; and (4) a model that predicts the next exhibit on the basis of inferred (rather than known) viewed exhibits. Our staged evaluation assesses the effect of these models (in combination with sensor noise) on inferential and predictive performance, thus shedding light on the reliability attributed to inferences drawn from sensor observations.

    Original languageEnglish
    Title of host publicationProceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems
    EditorsSarabjot Singh Anand, Dietmar Jannach, Bamshad Mobasher, Alfred Kobsa
    Place of PublicationAachen Germany
    PublisherCEUR-WS
    Pages49 - 56
    Number of pages8
    Volume756
    Publication statusPublished - 2011
    EventInternational Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP) 2011 - Barcelona, Spain
    Duration: 16 Jul 201116 Jul 2011
    Conference number: 9th

    Workshop

    WorkshopInternational Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP) 2011
    Abbreviated titleITWP 2011
    CountrySpain
    CityBarcelona
    Period16/07/1116/07/11

    Cite this

    Bohnert, F., Zukerman, I., Albrecht, D. W., & Baldwin, T. (2011). Modelling and predicting movements of museum visitors: A simulation framework for assessing the impact of sensor noise on model performance. In S. S. Anand, D. Jannach, B. Mobasher, & A. Kobsa (Eds.), Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems (Vol. 756, pp. 49 - 56). CEUR-WS.