[BibTeX] [RIS]
Evaluating Personalised Website Ranking Using Small Scale User Feedback: A User Study
Type of publication: Mastersthesis
Citation: ba:rahmouni
Type: Bachelor Thesis
Year: 2018
Month: October
School: TU Darmstadt, Knowledge Engineering Group
URL: https://www.ke.tu-darmstadt.de/lehre/arbeiten/bachelor/2018/Rahmouni_Khalil.pdf
Abstract: This thesis evaluates the ranking quality of a web browser extension search engine that uses explicit relevance feedback to learn a personalized model. A user study is conducted to collect a small scale data that will be used in the evaluation process and the comparison with classi?cation SVM and SVM Rank. We conclude that the learned personalized model enhances the ranking performance and outperforms the original rank, classi?cation SVM and SVM Rang in a small-scale data.
Userfields: betreuer={ELM}
Authors Rahmouni, Khalil