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Home    Visit Collage : generating digital journals to prolong the afterglow effect of visits in AmI exhibition spaces / Stavros Bastakis; thesis advisor, Prof. Constantine Stephanidis.  

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Identifier 000382405
Title Visit Collage : generating digital journals to prolong the afterglow effect of visits in AmI exhibition spaces / Stavros Bastakis; thesis advisor, Prof. Constantine Stephanidis.
Alternative Title Visit Collage : ψηφιακά ημερολόγια εμπειριών χρήσης σε εκθεσιακούς χώρους δίαχυτης νοημοσύνης
Author Μπαστάκης, Σταύρος
Thesis advisor Στεφανίδης, Κωνσταντίνος
Reviewer Πλεξουσάκης, Δημήτριος
Γραμμένος, Δημήτριος
Μπίλας, Άγγελος
Abstract In the last decade, the emerging domain of Ambient Intelligence influenced the introduction of innovative, even experimental, ubiquitous technologies in exhibition spaces. Exhibition spaces, and in particular museums, are constantly augmenting their spaces with digital installations, thus the necessity of systems that deliver context-sensitive information and tailored recommendations in order to create new and engaging forms of interactive experiences is even higher. The VisitCollage system proposed in this thesis aims to enhance the visitors’ experience and engagement in the ubiquitous exhibition space. The system provides facilities for capturing the visitors’ activity within the exhibition space in real time, as well as mechanisms for identifying visitors’ interests and behavior based on their activity. In addition, it supports the delivery of personalized recommendations of related exhibits, either physical or digital, based on the automatically inferred interests. The visitors’ interests along with the recommendations are visualized into personalized, dynamically generated web pages, thus conveying the on-site exhibition experience with digital content on-line. In order to achieve the above, the VisitCollage system provides an infrastructure of intelligent agents which unobtrusively monitor the visitors’ activity in a seamless manner, and exploiting the advantages of ontology-based modelling and rules-based reasoning, infers the visitors’ interests and recommendations. Advanced web technologies such as HTML5, CSS3 and JavaScript are utilized to “capture” the entire visit into dynamically generated, personalized journals where the captured content is visualized: (i) sequentially, ordered either chronologically or by interest, (ii) overlaid on top of a floor plan and (iii) as an elegant booklet.
Language English
Subject Ambient intelligence
Ontologies
Recommendations
Οντολογίες
Προτάσεις
Issue date 2014-03-28
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
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