Abstract
Social trust holds great potential for improving recommendation and much recent work focuses on the use of social trust for rating prediction, in particular, in the context of the Epinions dataset. An experimental comparison with trust-free, naïve approaches suggests that state-of-the-art social-trust-aware recommendation approaches, in particular Social Trust Ensemble (STE), can fail to isolate the true added value of trust. We demonstrate experimentally that not only trust-set users, but also random users can be exploited to yield recommendation improvement via STE. Specific users, however, do benefit from use of social trust, and we conclude with an investigation of their characteristics.
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© 2011 Springer-Verlag Berlin Heidelberg
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Shi, Y., Larson, M., Hanjalic, A. (2011). How Far Are We in Trust-Aware Recommendation?. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_75
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DOI: https://doi.org/10.1007/978-3-642-20161-5_75
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-20161-5
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