Abstract
In this paper we present a novel user-centered recommendation approach for multimedia art collections. In particular, preferences (usually coded in the shape of items’ metadata), opinions (textual comments to which it is possible to associate a particular sentiment), behavior (in the majority of cases logs of past items’ observations and actions made by users in the environment), and feedbacks (usually expressed in the form of ratings) are considered and integrated together with items’ features and context information within a general and unique recommendation framework that can support an intelligent browsing of any multimedia repository. Preliminary experiments show the utility of the proposed strategy to perform different browsing tasks.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
In the Cultural Heritage domain different harvesting sets of metadata and possibly domain taxonomies or ontologies can be considered.
- 2.
Note that a positive element \(a_{ij}^k\) of \(A^k\) indicates that \(o_i\) was accessed exactly k steps after \(o_j\) at least once.
- 3.
- 4.
Virtual rooms with paintings are related to specific historical periods.
- 5.
The suggested paths represent the most easy way for the player to find and access the paintings of interest.
References
Albanese, M., d’Acierno, A., Moscato, V., Persia, F., Picariello, A.: A multimedia recommender system. ACM Trans. Internet Techn. 13(1), 3 (2013)
Kabassi, K.: Personalisation systems for cultural tourism. In: Multimedia Services in Intelligent Environments, pp. 101–111. Springer (2013)
Karaman, S., Bagdanov, A.D., Landucci, L., D’Amico, G., Ferracani, A., Pezzatini, D., Del Bimbo, A.: Personalized multimedia content delivery on an interactive table by passive observation of museum visitors. Multimedia Tools Appl. 75(7), 3787–3811 (2016)
Colace, F., Santo, M.D., Greco, L., Moscato, V., Picariello, A.: A collaborative user-centered framework for recommending items in online social networks. Comput. Hum. Behav. 51, 694–704 (2015)
Albanese, M., d’Acierno, A., Moscato, V., Persia, F., Picariello, A.: A multimedia semantic recommender system for cultural heritage applications. In: Proceedings of the 5th IEEE International Conference on Semantic Computing (ICSC 2011), Palo Alto, CA, USA, 18–21 September, pp. 403–410 (2011)
Bartolini, I., Moscato, V., Pensa, R.G., Penta, A., Picariello, A., Sansone, C., Sapino, M.L.: Recommending multimedia visiting paths in cultural heritage applications. Multimedia Tools Appl. 75(7), 3813–3842 (2016)
Minutolo, A., Esposito, M., De Pietro, G.: A mobile reasoning system for supporting the monitoring of chronic diseases. Springer, Heidelberg, pp. 225–232 (2012)
Adomavicius, G., Sankaranarayanan, R., Sen, S., Tuzhilin, A.: Incorporating contextual information in recommender systems using a multidimensional approach. ACM Trans. Inf. Syst. (TOIS) 23(1), 103–145 (2005)
Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.): Recommender Systems Handbook. Springer (2011)
Essmaeel, K., Gallo, L., Damiani, E., De Pietro, G., Dipanda, A.: Comparative evaluation of methods for filtering kinect depth data. Multimedia Tools Appl. 74(17), 7331–7354 (2015)
Brancati, N., Caggianese, G., Frucci, M., Gallo, L., Neroni, P.: Experiencing touchless interaction with augmented content on wearable head-mounted displays in cultural heritage applications. In: Personal and Ubiquitous Computing, pp. 1–15
Caggianese, G., Gallo, L., De Pietro, G.: Design and preliminary evaluation of a touchless interface for manipulating virtual heritage artefacts. In: 2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems (SITIS), pp. 493–500. IEEE (2014)
Albanese, M., Chianese, A., d’Acierno, A., Moscato, V., Picariello, A.: A multimedia recommender integrating object features and user behavior. Multimedia Tools Appl. 50(3), 563–585 (2010)
Albanese, M., d’Acierno, A., Moscato, V., Persia, F., Picariello, A.: Modeling recommendation as a social choice problem. In: Proceedings of the 2010 ACM Conference on Recommender Systems, RecSys 2010, Barcelona, Spain, 26–30 September, pp. 329–332 (2010)
Amato, F., Mazzeo, A., Moscato, V., Picariello, A.: A framework for semantic interoperability over the cloud. In: Proceedings - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013, pp. 1259–1264 (2013)
Amato, F., Mazzeo, A., Penta, A., Picariello, A.: Using NLP and ontologies for notary document management systems. In: Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, pp. 67–71 (2008)
Bartolini, I., Patella, M.: Multimedia queries in digital libraries. In: Data Management in Pervasive Systems, pp. 311–325. Springer (2015)
Strang, T., Linnhoff-Popien, C.: A context modeling survey. In: Workshop Proceedings (2004)
Colantonio, S., Esposito, M., Martinelli, M., De Pietro, G., Salvetti, O.: A knowledge editing service for multisource data management in remote health monitoring. IEEE Trans. Inf. Technol. Biomed. 16(6), 1096–1104 (2012)
Hart, S.G., Staveland, L.E.: Development of nasa-tlx (task load index): Results of empirical and theoretical research. Adv. Psychol. 52, 139–183 (1988)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Amato, F., Moscato, V., Picariello, A., Sperlí, G. (2018). A Recommender System for Multimedia Art Collections. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-59480-4_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59479-8
Online ISBN: 978-3-319-59480-4
eBook Packages: EngineeringEngineering (R0)