Inproceedings,

A fast collaborative filtering algorithm for implicit binary data

, , and .
Computer-Aided Industrial Design Conceptual Design, 2009. CAID CD 2009. IEEE 10th International Conference on, page 973 -976. (November 2009)
DOI: 10.1109/CAIDCD.2009.5374935

Abstract

Item-based and user-based collaborative filtering are two well-known algorithms for recommender system in e-commerce. Both the algorithms make use of similarity matrix whose elements represent the similarity of each item pairs or user pairs. A fast algorithm for item-based similarity matrix computation using cosine similarity metric was reviewed and applied for user-based one with some modification. The results show that the fast algorithm can blend well with other similarity metrics, and it can greatly improve the computational performance.

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