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A new collaborative filtering approach for increasing the aggregate diversity of recommender systems
2013
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13
In order to satisfy and positively surprise its users, a recommender system needs to recommend items the users will like and most probably would not have found on their own. This requires the recommender system to recommend a broader range of items including niche items. Such an approach also supports online-stores that often offer more items than traditional stores and need recommender systems to enable users to find the not so popular items as well. However, popular items that hold a lot of
doi:10.1145/2487575.2487656
dblp:conf/kdd/NiemannW13
fatcat:plqs4lso4ngs7ap6jz4xstgjai