Modelling User Web Browsing Behaviour for Relevant Content-based Retrieval

Building a mathematical model of how user behaves on a website is a useful method for determining what a user does and does not like. This model allows for information relevant to a user to be presented without having the user go out and find the information by themselves. These types of systems, generally known as “recommender systems” allow websites to provide custom content to users without a user having to explicitly state what they are interested in. WhoThaMan wants to develop such a system so that users are presented with sports news articles that are relevant to them. WhoThaMan then provides a forum for users to debate current events in the field of professional sports, thereby generating content on their site. Knowing what a user likes allows WhoThaMan to tailor the news articles to the individual user and increase the chances that a user will contribute their opinions to the site.

Faculty Supervisor:

Dr. Androutsos

Student:

Richard Rzeszutek

Partner:

WhoThaMan Media

Discipline:

Engineering

Sector:

Information and communications technologies

University:

Ryerson University