CS 69191: Masters Seminar
CS 89191: Doctoral Seminar
Spring 2009
Masters Student Presentation:
Recommender Systems
James Van Heyde
Recommender systems provide ecommerce websites that have enormous
product catalogs to provide a better user experience for their
customers while at the same time bringing attention to less popular
catalog items that would otherwise remain in inventory. With these
systems customers are shown more relevant real time recommendations
for products that likely appeal to their individual interests. We will
examine two methods for recommending items to users, one from
Amazon.com and the other from the BellKor submission to the Netflix
Prize. The Amazon model uses an item-item recommendation engine while
the Netflix Prize model uses a hybrid approach that implements pieces
of the item-item along with other more traditional user-user
techniques. Both techniques are extremely effective under real world
situations in which the user input only represents a very small sample
size of the overall data set.