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
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.
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