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- W2904605601 abstract "With the proliferation of services on the web, it is increasingly vital to recommend services that best meet users' requirements. Collaborative filtering has been successfully used for service recommendation. However, it still faces two challenges: 1) to infer user interest from the service level is imprecise as a user often only calls several operations of a service; and 2) to calculate user interest similarity based on the sparse rating data is inaccurate as there are not enough co-rated services. In view of these challenges, an operation-level collaborative filtering approach based on Logistic function is proposed in this paper. First, according to the number of service operation calls, a user preference is calculated by a Logistic function. Then, collaborative filtering based on the usage preference rather than based on the sparse ratings is implemented for service recommendation. The effectiveness of this approach is verified by some experiments." @default.
- W2904605601 created "2018-12-22" @default.
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- W2904605601 date "2018-10-01" @default.
- W2904605601 modified "2023-10-14" @default.
- W2904605601 title "An Operation-Level Collaborative Filtering Approach Based on Logistic Function for Web Services Recommendation" @default.
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- W2904605601 doi "https://doi.org/10.1109/smartworld.2018.00189" @default.
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