by Benjamin Heitmann, Conor Hayes
Abstract:
While recommender systems can greatly enhance the user experience, the entry barriers in terms of data acquisition are very high, making it hard for new service providers to compete with existing recommendation services. This paper proposes to build open recommender systems which can utilise Linked Data to mitigate the new-user, new-item and sparsity problems of collaborative recommender systems. We describe how to aggregate data about object centred sociality from different sources and how to process it for collaborative recommendation. To demonstrate the validity of our approach, we augment the data from a closed collaborative music recommender system with Linked Data, and significantly improve its precision and recall.
Reference:
Using linked data to build open, collaborative recommender systems (Benjamin Heitmann, Conor Hayes), In Artificial Intelligence, 2010.
Bibtex Entry:
@article{Heitmann2010,
abstract = {While recommender systems can greatly enhance the user experience, the entry barriers in terms of data acquisition are very high, making it hard for new service providers to compete with existing recommendation services. This paper proposes to build open recommender systems which can utilise Linked Data to mitigate the new-user, new-item and sparsity problems of collaborative recommender systems. We describe how to aggregate data about object centred sociality from different sources and how to process it for collaborative recommendation. To demonstrate the validity of our approach, we augment the data from a closed collaborative music recommender system with Linked Data, and significantly improve its precision and recall.},
author = {Heitmann, Benjamin and Hayes, Conor},
journal = {Artificial Intelligence},
keywords = {SML-LIB-BIBLIO,lang:ENG,technical report ss 10 07},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
pages = {76--81},
title = {{Using linked data to build open, collaborative recommender systems}},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.2755 http://www.aaai.org/ocs/index.php/SSS/SSS10/paper/viewPDFInterstitial/1067/1452},
year = {2010}
}