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Multimedia Tools and Applications

, Volume 58, Issue 1, pp 167–213 | Cite as

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

  • Toon De PessemierEmail author
  • Sam Coppens
  • Kristof Geebelen
  • Chris Vleugels
  • Stijn Bannier
  • Erik Mannens
  • Kris Vanhecke
  • Luc Martens
Article

Abstract

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation.

Keywords

Recommender system Personalization Event modeling Distributing event information 

Notes

Acknowledgements

The research activities that have been described in this paper were funded by Ghent University, K.U. Leuven, VUB, VRT-medialab, Interdisciplinary Institute for Broadband Technology (IBBT) through the CUPID project (50% co-funded by industrial partners), the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), the Fund for Scientific Research-Flanders (FWO-Flanders), and the European Union.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Toon De Pessemier
    • 1
    Email author
  • Sam Coppens
    • 2
  • Kristof Geebelen
    • 3
  • Chris Vleugels
    • 4
  • Stijn Bannier
    • 4
  • Erik Mannens
    • 2
  • Kris Vanhecke
    • 1
  • Luc Martens
    • 1
  1. 1.INTEC – WiCaGhent University – IBBTGhentBelgium
  2. 2.ELIS – Multimedia LabGhent University – IBBTGhentBelgium
  3. 3.DistrinetK.U. Leuven – IBBTLeuvenBelgium
  4. 4.SMITVUB – IBBTBrusselsBelgium

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