This paper presents a semantic recommender method and a system for a personalized access to digital cultural heritage through context-aware user profiling. Given annotation knowledge-bases, explicit background knowledge in the form of ontologies, a user model capturing the user’s behavior and context, the system produces recommendations. Ontology-based user profiling can be used to reduce cold-start, sparsity and over-specialization problems. In addition, we present a recommendation retrieval method that is based on the vector space model and uses indices that enable fast and scalable implementation of the system.
%0 Journal Article
%1 Ruotsalo09smartmuseum--
%A Ruotsalo, Tuukka
%A Mäkelä, Eetu
%A Kauppinen, Tomi
%A Hyvönen, Eero
%A Haav, Krister
%A Rantala, Ville
%A Frosterus, Matias
%A Dokoohaki, Nima
%A Matskin, Mihhail
%D 2009
%K access aware context cultural heritage personalized recommendation recommender smartmuseum system
%T Smartmuseum -- Personalized Context-aware Access to Digital Cultural Heritage
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.9014
%X This paper presents a semantic recommender method and a system for a personalized access to digital cultural heritage through context-aware user profiling. Given annotation knowledge-bases, explicit background knowledge in the form of ontologies, a user model capturing the user’s behavior and context, the system produces recommendations. Ontology-based user profiling can be used to reduce cold-start, sparsity and over-specialization problems. In addition, we present a recommendation retrieval method that is based on the vector space model and uses indices that enable fast and scalable implementation of the system.
@article{Ruotsalo09smartmuseum--,
abstract = { This paper presents a semantic recommender method and a system for a personalized access to digital cultural heritage through context-aware user profiling. Given annotation knowledge-bases, explicit background knowledge in the form of ontologies, a user model capturing the user’s behavior and context, the system produces recommendations. Ontology-based user profiling can be used to reduce cold-start, sparsity and over-specialization problems. In addition, we present a recommendation retrieval method that is based on the vector space model and uses indices that enable fast and scalable implementation of the system. },
added-at = {2012-10-10T11:25:04.000+0200},
author = {Ruotsalo, Tuukka and Mäkelä, Eetu and Kauppinen, Tomi and Hyvönen, Eero and Haav, Krister and Rantala, Ville and Frosterus, Matias and Dokoohaki, Nima and Matskin, Mihhail},
biburl = {https://www.bibsonomy.org/bibtex/28c4a94d7348573f0c94f85e19dbfe806/nimdoc},
interhash = {5d2f922be40f8f0390e2905c834a915f},
intrahash = {8c4a94d7348573f0c94f85e19dbfe806},
keywords = {access aware context cultural heritage personalized recommendation recommender smartmuseum system},
timestamp = {2012-10-10T11:25:04.000+0200},
title = {Smartmuseum -- Personalized Context-aware Access to Digital Cultural Heritage},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.9014},
year = 2009
}