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Social Recommender Systems

  • Alireza RezvanianEmail author
  • Behnaz Moradabadi
  • Mina Ghavipour
  • Mohammad Mehdi Daliri Khomami
  • Mohammad Reza Meybodi
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 820)

Abstract

Due to the incredible growth of information on the World Wide Web in the recent years, searching and finding contents, products or services that may be of interest for users has become a very difficult task. Recommender systems (RSs) help overcome the information overload problem by studying the preferences of online users and suggesting items they might like. Many companies and Web sites have implemented these systems to recommend products/information/services to their users in a more accurate manner, therefore improving the company’s profits. In this chapter, first we give a brief review on social recommender systems and then we introduce sevela learning automata-based recommended systems.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alireza Rezvanian
    • 1
    • 2
    Email author
  • Behnaz Moradabadi
    • 2
  • Mina Ghavipour
    • 2
  • Mohammad Mehdi Daliri Khomami
    • 2
  • Mohammad Reza Meybodi
    • 2
  1. 1.School of Computer ScienceInstitute for Research in Fundamental Sciences (IPM)TehranIran
  2. 2.Computer Engineering and Information Technology DepartmentAmirkabir University of Technology (Tehran Polytechnic)TehranIran

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