An integrated model for evaluation of big data challenges and analytical methods in recommender systems

An integrated model for evaluation of big data challenges and analytical methods in recommender systems

Abstract The study aimed to present an integrated model for evaluation of big data (BD) challenges and analytical methods in recommender systems (RSs). The proposed model used fuzzy multi-criteria decision making (MCDM) which is a human judgment-based method for weighting of RSs’ properties. Human j...

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Bibliographic Details
Main Authors: Adeleh Asemi, Asefeh Asemi, Andrea Ko, Ali Alibeigi
Format: Article
Language:English
Published: SpringerOpen 2022-01-01
Series:Journal of Big Data
Subjects:
Recommender system properties
Big Data properties
Dig Data challenges
Analytical methods
Fuzzy multi-criteria decision making
Fuzzy AHP
Online Access:https://doi.org/10.1186/s40537-022-00560-z

Internet

https://doi.org/10.1186/s40537-022-00560-z

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