Extending Recommender Systems: A Multidimensional Approach
نویسندگان
چکیده
In this paper, we present new extensions to traditional approaches to recommender systems by making recommender systems support data warehousing capabilities. In particular, we propose recommender systems to work in multidimensional settings as opposed to the traditional twodimensional user/item environments. We also propose recommender systems to support rich profiling and OLAP capabilities.
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تاریخ انتشار 2001