In this paper we present a novel method of comparing instances of ontological concepts in regard to personalized presentation
and/or navigation in large information spaces. It is based on the assumption that comparing attributes of documents whichwere found interesting for a user can be a source for discovering information about user’s interests. We consider applicationsfor the Semantic Web where documents or their parts are represented by ontological concepts. We employ ontology structureand different similarity metrics for data type and object type attributes. From personalization point of view we impute reasonsthat might have caused user’s interest in the content. Moreover, we propose a way to enumerate similarity for the particularuser while taking into account individual user’s interests and preferences.
%0 Journal Article
%1 keyhere
%A Andrejko, Anton
%A Bieliková, Mária
%D 2008
%J Artificial Neural Networks - ICANN 2008
%K imported ontology
%P 1--10
%T Investigating Similarity of Ontology Instances and Its Causes
%U http://dx.doi.org/10.1007/978-3-540-87559-8_1
%X In this paper we present a novel method of comparing instances of ontological concepts in regard to personalized presentation
and/or navigation in large information spaces. It is based on the assumption that comparing attributes of documents whichwere found interesting for a user can be a source for discovering information about user’s interests. We consider applicationsfor the Semantic Web where documents or their parts are represented by ontological concepts. We employ ontology structureand different similarity metrics for data type and object type attributes. From personalization point of view we impute reasonsthat might have caused user’s interest in the content. Moreover, we propose a way to enumerate similarity for the particularuser while taking into account individual user’s interests and preferences.
@article{keyhere,
abstract = {In this paper we present a novel method of comparing instances of ontological concepts in regard to personalized presentation
and/or navigation in large information spaces. It is based on the assumption that comparing attributes of documents whichwere found interesting for a user can be a source for discovering information about user’s interests. We consider applicationsfor the Semantic Web where documents or their parts are represented by ontological concepts. We employ ontology structureand different similarity metrics for data type and object type attributes. From personalization point of view we impute reasonsthat might have caused user’s interest in the content. Moreover, we propose a way to enumerate similarity for the particularuser while taking into account individual user’s interests and preferences.},
added-at = {2009-02-11T10:32:31.000+0100},
author = {Andrejko, Anton and Bieliková, Mária},
biburl = {https://www.bibsonomy.org/bibtex/28ca5c7ea1bf58ea7eb5fe7cc8245af2a/okohonen},
description = {SpringerLink - Book Chapter},
interhash = {7de4b8519c8e7f1d46650984c9514066},
intrahash = {8ca5c7ea1bf58ea7eb5fe7cc8245af2a},
journal = {Artificial Neural Networks - ICANN 2008},
keywords = {imported ontology},
pages = {1--10},
timestamp = {2009-02-11T10:32:31.000+0100},
title = {Investigating Similarity of Ontology Instances and Its Causes},
url = {http://dx.doi.org/10.1007/978-3-540-87559-8_1},
year = 2008
}