A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Refining User and Item Profiles based on Multidimensional Data for Top-N Item Recommendation
2014
Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services - iiWAS '14
In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for
doi:10.1145/2684200.2684284
dblp:conf/iiwas/TangXG14
fatcat:od7nqrm5xjbw5c2wkdwkxelp24