Abstract
The recently introduced TREC Contextual Suggestion track proposes the problem of suggesting contextually relevant places to a user visiting a new city based on his/her preferences and the location of the new city. In this paper we introduce a more sophisticated approach to this problem which very carefully constructs user profiles in order to provide more accurate and relevant recommendations. Based on the track evaluations we demonstrate that our system not only significantly outperforms a baseline method but also performs very well in comparison to other runs submitted to the track, managing to achieve the best results in nearly half of all test contexts.
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Rikitianskii, A., Harvey, M., Crestani, F. (2014). A Personalised Recommendation System for Context-Aware Suggestions. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_6
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DOI: https://doi.org/10.1007/978-3-319-06028-6_6
Publisher Name: Springer, Cham
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