PhD Comprehensive Examination Announcement of Bahareh Rahmatikargar:"Current trends and challenges in recommendation systems"

Monday, December 19, 2022 - 15:00 to 16:30


The School of Computer Science would like to present…   

Ph.D Comprehensive Exam by: Bahareh Rahmatikargar 

Date: Monday, December 19, 2022 
Time: 3:00 pm-4:30 pm 
Location: Essex Hall, Room 122 


The idea of recommendation systems emerged mainly as a novel solution to the information overload problem. Up to now, numerous recommendation system methodologies have been put forth, and a variety of recommendation system software has been created for a wide range of applications. Nowadays, managers and researchers recognize that recommendation systems present significant opportunities and challenges for the business, government, educational, and other domains. Moreover, the need for the successful development of recommendation systems for real-world applications is also becoming apparent. Therefore, it is essential to conduct a high-quality review of current trends, and challenges. Lack of explainability is one of the challenges such systems face. To solve the issue explainable recommendation systems are created. These systems give users or system designers explanations along with the recommendation results. In this way, they contribute to increasing the recommendation systems’ transparency, persuasiveness, effectiveness, trustworthiness, and user satisfaction. Additionally, they make it easier for system designers to diagnose, debug, and refine the recommendation algorithm.  
In this talk, I will first present a high-level overview of the recommendation system and its applications. Then I discuss different types of recommendation systems (for example graph-based, session-based, etc.) and their challenges. Finally, explainable recommendation systems will be discussed. Moreover, some of the most famous datasets in the field and evaluation metrics will be reviewed. 
Recommendation systems, applications, challenges, explainable recommendation systems 

PhD Doctoral Committee: 

External Reader: Dr. Mitra Mirhassani  
Internal Reader: Dr. Dan Wu 
Internal Reader: Dr. Saeed Samet 
Advisor(s): Dr. Pooya Moradian Zadeh, Dr. Ziad Kobti 



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