Fast Recommendations With the M-Distance

Fast Recommendations With the M-Distance

Memory-based recommender systems with m users and n items typically require O(mn) space to store the rating information. In item-based collaborative filtering (CF) algorithms, the feature vector of each item has length m,and it takes O(m) time to compute the similarity between two items using the Pe...

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Bibliographic Details
Main Authors: Mei Zheng, Fan Min, Heng-Ru Zhang, Wen-Bin Chen
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Computational complexity
distance measure
neighborhood
recommender systems
Online Access:https://ieeexplore.ieee.org/document/7452337/

Internet

https://ieeexplore.ieee.org/document/7452337/

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