Implikat : A System for Categorizing Products using Implicit Feedback on a Website

Abstract: Implicit feedback is a form a relevance feedback that is inferred from how users interact with an information retrieval system such as an online search engine. This degree project report describes a method of using implicit feedback to establish relevance judgments and rank products based on their relevance to a specified attribute. The report contains an overview of the benefits and limitations of implicit feedback, as well as a description on how those limitations can be mitigated. A prototype that interpreted user actions as relevance votes and calculat-ed a fair relevance score based on these votes with the help of an algo-rithm was developed. This system was then tested on a website with real users during a limited period of time. The results from the test period were evaluated and the system was concluded to be far from perfect, but that improvements could be made by making adjustments to the algo-rithm. The system performed better when looking at the algorithm’s pre-cision rather than its sensitivity.