BRS c S: a hybrid recommendation model fusing multi-source heterogeneous data

BRS c S: a hybrid recommendation model fusing multi-source heterogeneous data

Abstract Recommendation systems are often used to solve the problem of information overload on the Internet. Many types of data can be used for recommendations, and fusing different types of data can make recommendations more accurate. Most existing fusion recommendation models simply combine the re...

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Bibliographic Details
Main Authors: Zhenyan Ji, Chun Yang, Huihui Wang, José Enrique Armendáriz-iñigo, Marta Arce-Urriza
Format: Article
Language:English
Published: SpringerOpen 2020-06-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Multi-source heterogeneous data
Recommendation model
Social network
Online Access:http://link.springer.com/article/10.1186/s13638-020-01716-2

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http://link.springer.com/article/10.1186/s13638-020-01716-2

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