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Mining recommendations from the web

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Proceedings of the 2008 ACM conference on Recommender systems, стр. 35--42. New York, NY, USA, ACM, (2008)
DOI: 10.1145/1454008.1454015

Аннотация

In this paper we study the challenges and evaluate the effectiveness of data collected from the web for recommendations. We provide experimental results, including a user study, showing that our methods produce good recommendations in realistic applications. We propose a new evaluation metric, that takes into account the difficulty of prediction. We show that the new metric aligns well with the results from a user study.

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