Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A fast collaborative filtering algorithm for implicit binary data
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.
A fast collaborative filtering algorithm for implicit binary data
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.
A fast collaborative filtering algorithm for implicit binary data
Manzhao Bu, (Autor:in) / Shijian Luo, (Autor:in) / Ji He, (Autor:in)
01.11.2009
109080 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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