A two-stage location-sensitive and user preference-aware recommendation system
作者：
Highlights：
• Increasing the accuracy in estimating the quantitative/qualitative factors of service.
• Services with the least response time and the highest level of confidentiality.
• Supporting the expressed needs of cloud customers verbally and numerically.
摘要
•Increasing the accuracy in estimating the quantitative/qualitative factors of service.•Services with the least response time and the highest level of confidentiality.•Supporting the expressed needs of cloud customers verbally and numerically.
论文关键词：Cloud service recommendation system,Decision making,Fuzzy set theory,Cloud service selection,Neural-fuzzy models
论文评审过程：Received 10 September 2020, Revised 29 October 2021, Accepted 30 October 2021, Available online 24 November 2021, Version of Record 1 December 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.116188
