CBRS: CURIOSITY BASED RECOMMENDATION SYSTEM

PhD Thesis Proposal Defence


Title: "CBRS: CURIOSITY BASED RECOMMENDATION SYSTEM"

by

Mr. Pengfei ZHAO


Abstract:

Traditional recommendation systems (RSs) aim to recommend items that are 
relevant to the user’s historical interest. They fail to arouse users’ 
interest in the recommendations because the recommendations soon become 
very familiar to the users. Discovery-oriented recommendation systems 
(DORSs) complement accuracy with discover utilities (DUs) such as novelty 
and diversity to entice users to explore beyond their interests by 
optimizing the DUs and the accuracy of the recommendations. Unfortunately, 
DORSs ignore an important fact that different users have different 
appetite for DUs. That is, highly curious users can accept highly novel 
and diversified recommendations whereas conservative users would behave in 
the opposite manner.

We propose a curiosity-based recommendation system (CBRS) framework which 
generates recommendations with a personalized amount of DUs to fit the 
user’s curiosity level. We propose a computational model of user 
curiosity, called Probabilistic Curiosity Model (PCM), which is based on 
the curiosity arousal theory and Wundt curve in psychology research. In 
PCM, we model a user’s curiosity with a curiosity distribution function 
learnt from the user’s access history and compute a curiousness score for 
each item representing how curious the user is about the item. CBRS then 
selects items which are both relevant and have high curiousness score, 
bounded by the constraint that the amount of DUs fits the user’s DU 
appetite. We use joint optimization and co-factorization approaches to 
incorporate the curiosity signal into RSs. We provide experimental results 
to demonstrate the effectiveness of CBRS.

Finally, we discuss future research directions for extending the proposed 
curiosity model.


Date:			Thursday, 25 February 2016

Time:                  	2:30pm - 4:30pm

Venue:                  Room 1504
                         lifts 25/26

Committee Members:	Prof. Dik-Lun Lee (Supervisor)
  			Dr. Raymond Wong (Chairperson)
 			Dr. Wilfred Ng
  			Dr. Ke Yi


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