Improving a User-focused Product Recommender System by optimally utilizing User Input
|has title::Improving a User-focused Product Recommender System by optimally utilizing User Input|
|Master:||project within::Information Sciences|
|Student name:||student name::T. Pellikaan|
A new method of online product comparison and recommendation has been developed by the graduating student. This method is much more user-focused than current solutions and is innovative in its way of supporting the decision making process and eliminating information and choice overload. The system is based on the method of multi-dimensional similarity scaling. This method recommends more similar products to a product that is selected by the user. However, this system needs to be more specified in terms of technical implementation and algorithm design. This will be the goal of the graduation project. It will be researched which methods exist to utilize user input to offer personalized recommendations. Secondly, ways of making the system learn from interactions with the user will be explored. A technical design will be developed based on this research.