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AI & SOCIETY

pp 1–15 | Cite as

Presenting a hybrid model in social networks recommendation system architecture development

  • Abolfazl ZareEmail author
  • Mohammad Reza Motadel
  • Aliakbar Jalali
Student Forum
  • 40 Downloads

Abstract

There are many studies conducted on recommendation systems, most of which are focused on recommending items to users and vice versa. Nowadays, social networks are complicated due to carrying vast arrays of data about individuals and organizations. In today’s competitive environment, companies face two significant problems: supplying resources and attracting new customers. Even the concept of supply-chain management in a virtual environment is changed. In this article, we propose a new and innovative combination approach to recommend organizational people in social networks based on organizational communication and SCM. The proposed approach uses a hybrid strategy that combines basic collaborative filtering and demographic recommendation systems, using data mining, artificial neural networks, and fuzzy techniques. The results of experiments and evaluations based on a real dataset collected from the LinkedIn social network showed that the hybrid recommendation system has higher accuracy and speed than other essential methods, even substantially has eliminated the fundamental problems with such systems, such as cold start, scalability, diversity, and serendipity.

Keywords

Recommendation systems Collaborative filtering Artificial neural network Fuzzy logic Supply-chain management Social networks 

Abbreviations

RS

Recommendation systems

SCM

Supply-chain management

ANN

Artificial neural networks

CF-RS

Collaborative filtering RS

D-RS

Demographic RS

CB-RS

Content-based RS

DM

Data mining

ED

Euclidean distance

MF

Membership function

MAE

Mean absolute error

RMSE

Root mean squared error

FPR

False-positive rate

TPR

True-positive rate

OM

Overlap measure

Notes

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Management, Central Tehran BranchIslamic Azad UniversityTehranIran
  2. 2.Department of Computer ScienceUniversity of MarylandCollege ParkUSA

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