Context-Aware Recommender System: A Survey

PhD Qualifying Examination


Title: "Context-Aware Recommender System: A Survey"

by

Miss Lili ZHAO


Abstract:

Recommender systems are intelligent tools that help users to navigate among a 
huge selection of items to meet variety of special needs and tastes. Recent 
advances of recommender systems benefits from the Collaborative Filtering (CF) 
techniques, which are modeled on user-item ratings. With the huge and ever 
increasing volume of various contextual information available, new scenarios 
for recommendations are emerging that offer new information going beyond 
user-item ratings. In many applications, it is important to incorporate the 
contextual information into the recommendation process. For example, using 
user's location context, recommender system would provide a recommendation that 
can be more useful than the one without considering such context.

The context in recommender systems can be divided into three categories in 
terms of its resource type: attribute context information associated with users 
and items, user-item interaction related to interplay of users and items 
different from that encoded in rating matrix, and cross-domain context 
concerning knowledge from different but related domain. In this survey, we 
first introduce CF tasks and two main categories of CF techniques: 
memory-based, model-based. We then summarize and analyze recommendation 
scenarios involving contextual information and CF algorithms that have been 
recently proposed to address such conditions. We present a comprehensive 
introduction to a large body of research work, analysis of their predictive 
performance , with the aim of letting us better characterize, categorize and 
further develop recommender system by applying contextual information. At the 
end,  we conclude this survey and attempt to point out with what we see as 
central challenges lying ahead for this area.


Date:			Monday, 26 October 2015

Time:                  	3:00pm - 5:00pm

Venue:                  Room 2406
                         Lifts 17/18

Committee Members:	Prof. Qiang Yang (Supervisor)
 			Prof. James Kwok (Chairperson)
 			Dr. Wilfred Ng
 			Dr. Raymond Wong


**** ALL are Welcome ****