Abstract
Recommender systems in online marketing websites like Amazon.com and CDNow.com suggest relevant services and favorite products to customers. In this paper, we proposed a novel hypergraph-based kernel computation combined with k nearest neighbor (kNN) to predict ratings of users. In this method, we change regular definition style of hypergraph diffusion kernel. Our comparative studies show that our method performs better than typical kNN, which is simple and appropriate for online recommending applications.
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Kaveh-Yazdy, F., Kong, X., Li, J., Li, F., Xia, F. (2013). Customer Rating Prediction Using Hypergraph Kernel Based Classification. In: Yoshida, T., Kou, G., Skowron, A., Cao, J., Hacid, H., Zhong, N. (eds) Active Media Technology. AMT 2013. Lecture Notes in Computer Science, vol 8210. Springer, Cham. https://doi.org/10.1007/978-3-319-02750-0_19
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DOI: https://doi.org/10.1007/978-3-319-02750-0_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02749-4
Online ISBN: 978-3-319-02750-0
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