• Corpus ID: 235731933

Learning Complex Users' Preferences for Recommender Systems

  title={Learning Complex Users' Preferences for Recommender Systems},
  author={Shahpar Yakhchi},
  • S. Yakhchi
  • Published 4 July 2021
  • Computer Science
  • ArXiv
Recommender systems (RSs) have emerged as very useful tools to help customers with their decision-making process, find items of their interest, and alleviate the information overload problem. There are two different lines of approaches in RSs: (1) general recommenders with the main goal of discovering long-term users' preferences, and (2) sequential recommenders with the main focus of capturing short-term users' preferences in a session of user-item interaction (here, a session refers to a…