Collaborative recommendation algorithm based on contribution factor

A collaborative recommendation algorithm based on KNN didn't take in count the neighbours that blindly followed others, ideas, which made the neighbours useless to predicte the rates of the target users to the unknown items. To address this problem, this paper put forward the contribution facto...

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Bibliographic Details
Published inJi suan ji ying yong yan jiu Vol. 32; no. 12; pp. 3551 - 3554
Main Authors Wang, Xingmao, Zhang, Xingming
Format Journal Article
LanguageChinese
Published 01.12.2015
Subjects
Accuracy
Algorithms
Counting
Recommendations
Recommender systems
Similarity
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Summary:A collaborative recommendation algorithm based on KNN didn't take in count the neighbours that blindly followed others, ideas, which made the neighbours useless to predicte the rates of the target users to the unknown items. To address this problem, this paper put forward the contribution factor, thought over the non-common evaluation items, considered the contribution of neighbour recommendation, and selected the neighbours with the traditional similarity. And it recalculated the neighbour prediction weights to the unknown projects to advance the performance of recommendation. The experiments show that this algorithm improves the degree of accuracy.
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ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2015.12.005