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Recommending multimedia visiting paths in cultural heritage applications

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Abstract

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users—i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user’s satisfaction and system accuracy.

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Notes

  1. For multimedia feature extraction and mining, good surveys are [19, 24, 53].

  2. http://www-db.deis.unibo.it/Windsurf/

  3. http://telegraph.cs.berkeley.edu/tinydb/software.html

  4. TLX [26] is a multi-dimensional rating procedure that provides an overall score based on a weighted average of ratings provided by users by means of proper questionnaires on six sub-scales: mental demand, physical demand, temporal demand, own performance, effort and frustration. The lower TLX scores (ranging in the 0–100 interval), the better they are.

  5. We have chosen two groups of users among students and graduate students: the first one used the system for 3 weeks without recommendation facilities to capture a significant number of browsing sessions/ratings and then we asked the second one to indicate, for each target object (randomly selected), the most relevant ones among 100 multimedia items (belonging to the same POI of the target one) rating each one in a scale ranging from 1 to 5.

  6. www.databenc.it

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Acknowledgments

The realization of the proposed prototype was supported by DATABENC,Footnote 6 a high technology district for Cultural Heritage management recently funded by Regione Campania - Italy.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Bologna, Viale Risorgimento 2, 40136, Bologna, Italy

    Ilaria Bartolini

  2. Department of Electrical Engineering and Information Technology, University of Naples Federico II, via Clusio 21, 80125, Naples, Italy

    Vincenzo Moscato, Antonio Picariello & Carlo Sansone

  3. Department of Computer Science, University of Torino, Corso Svizzera 185, 10149, Torino, Italy

    Ruggero G. Pensa, Antonio Penta & Maria Luisa Sapino

Authors
  1. Ilaria Bartolini
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  2. Vincenzo Moscato
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  3. Ruggero G. Pensa
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  4. Antonio Penta
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  5. Antonio Picariello
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  6. Carlo Sansone
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  7. Maria Luisa Sapino
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Correspondence to Ilaria Bartolini.

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Bartolini, I., Moscato, V., Pensa, R.G. et al. Recommending multimedia visiting paths in cultural heritage applications. Multimed Tools Appl 75, 3813–3842 (2016). https://doi.org/10.1007/s11042-014-2062-7

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  • DOI: https://doi.org/10.1007/s11042-014-2062-7

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