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2006
Springer

Ways of Computing Diverse Collaborative Recommendations

10 years 29 days ago
Ways of Computing Diverse Collaborative Recommendations
Abstract. Conversational recommender systems adapt the sets of products they recommend in light of user feedback. Our contribution here is to devise and compare four different mechanisms for enhancing the diversity of the recommendations made by collaborative recommenders. Significantly, we increase diversity using collaborative data only. We find that measuring the distance between products using Hamming Distance is more effective than using Inverse Pearson Correlation.
Derek G. Bridge, John Paul Kelly
Added 13 Jun 2010
Updated 13 Jun 2010
Type Conference
Year 2006
Where AH
Authors Derek G. Bridge, John Paul Kelly
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