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IteRank: An iterative network-oriented approach to neighbor-based collaborative ranking
[article]
2018
arXiv
pre-print
Neighbor-based collaborative ranking (NCR) techniques follow three consecutive steps to recommend items to each target user: first they calculate the similarities among users, then they estimate concordance of pairwise preferences to the target user based on the calculated similarities. Finally, they use estimated pairwise preferences to infer the total ranking of items for the target user. This general approach faces some problems as the rank data is usually sparse as users usually have
arXiv:1811.01345v1
fatcat:hajb7zitzjawjbdvjldiasymky