1st International ICST Workshop on Innovative Mobile User Interactivity

Research Article

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

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  • @INPROCEEDINGS{10.1007/978-3-642-12607-9_29,
        author={Wolfgang Woerndl and Henrik Muehe and Stefan Rothlehner and Korbinian Moegele},
        title={Context-Aware Recommendations in Decentralized, Item-Based Collaborative Filtering on Mobile Devices},
        proceedings={1st International ICST Workshop on Innovative Mobile User  Interactivity},
        proceedings_a={IMUI},
        year={2012},
        month={10},
        keywords={collaborative filtering context mobile guides item-based collaborative filtering},
        doi={10.1007/978-3-642-12607-9_29}
    }
    
  • Wolfgang Woerndl
    Henrik Muehe
    Stefan Rothlehner
    Korbinian Moegele
    Year: 2012
    Context-Aware Recommendations in Decentralized, Item-Based Collaborative Filtering on Mobile Devices
    IMUI
    Springer
    DOI: 10.1007/978-3-642-12607-9_29
Wolfgang Woerndl1,*, Henrik Muehe1,*, Stefan Rothlehner2,*, Korbinian Moegele1,*
  • 1: Technische Universitaet Muenchen
  • 2: EXO Exhibition Overview, c/o Lehrstuhl fuer Baurealisierung und Bauinformatik
*Contact email: woerndl@in.tum.de, muehe@in.tum.de, rothlehn@in.tum.de, moegele@in.tum.de

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.