LSH-based private data protection for service quality with big range in distributed educational service recommendations

LSH-based private data protection for service quality with big range in distributed educational service recommendations

Abstract Service recommendation has become a promising way to extract useful or valuable information from big educational data collected by various sensors and distributed in different platforms. How to protect the private user data in each cluster during recommendation processes is an interesting b...

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Bibliographic Details
Main Authors: Chao Yan, Xuening Chen, Qinglei Kong
Format: Article
Language:English
Published: SpringerOpen 2019-04-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Recommender system
Cluster
Sensor
Service quality with big range
Privacy preservation
Online Access:http://link.springer.com/article/10.1186/s13638-019-1407-3

Internet

http://link.springer.com/article/10.1186/s13638-019-1407-3

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