Improving a User-focused Product Recommender System by optimally utilizing User Input

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has title::Improving a User-focused Product Recommender System by optimally utilizing User Input
status: finished
Master: project within::Information Sciences
Student name: student name::T. Pellikaan
Dates
Start start date:=2012/03/01
End end date:=2012/10/31
Supervision
Supervisor: Michel Klein
Thesis: has thesis::Media:Thesis.pdf
Poster: has poster::Media:Posternaam.pdf

Signature supervisor



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Abstract

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.