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Context-Aware Recommendations in Decentralized, Item-Based Collaborative Filtering on Mobile Devices

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 35)

Abstract

The goal of the work presented in this paper is to design a context-aware recommender system for mobile devices. The approach is based on decentralized, item-based collaborative filtering on Personal Digital Assistants (PDAs). The already implemented system exchanges rating vectors among PDAs, computes local matrices of item similarity and utilizes them to generate recommendations. We then explain how to contextualize this recommender system according to the current time and position of the user. The idea is to use a weighted combination of the collaborative filtering score with a context score function. We are currently working on applying this approach in real world scenarios.

Keywords

  • collaborative filtering
  • context
  • mobile guides
  • item-based collaborative filtering

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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Woerndl, W., Muehe, H., Rothlehner, S., Moegele, K. (2010). Context-Aware Recommendations in Decentralized, Item-Based Collaborative Filtering on Mobile Devices. In: Phan, T., Montanari, R., Zerfos, P. (eds) Mobile Computing, Applications, and Services. MobiCASE 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12607-9_29

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  • DOI: https://doi.org/10.1007/978-3-642-12607-9_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12606-2

  • Online ISBN: 978-3-642-12607-9

  • eBook Packages: Computer ScienceComputer Science (R0)