Inferring User's Preferences Using Ontologies
Abstract
We consider recommender systems that filter information and only show the most preferred items. Good recommendations can be provided only when an accurate model of the user’s preferences is available. We propose a novel technique for filling in missing elements of a user’s preference model us-ing the knowledge captured in an ontology. Furthermore, we show through experiments on the MovieLens data set that our model achieves a high prediction accuracy and personaliza-tion level when little about the user’s preferences is known.
Cite
Text
Schickel-Zuber and Faltings. "Inferring User's Preferences Using Ontologies." AAAI Conference on Artificial Intelligence, 2006.Markdown
[Schickel-Zuber and Faltings. "Inferring User's Preferences Using Ontologies." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/schickelzuber2006aaai-inferring/)BibTeX
@inproceedings{schickelzuber2006aaai-inferring,
title = {{Inferring User's Preferences Using Ontologies}},
author = {Schickel-Zuber, Vincent and Faltings, Boi},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2006},
pages = {1413-1418},
url = {https://mlanthology.org/aaai/2006/schickelzuber2006aaai-inferring/}
}