@inproceedings{breit-2020-interlinking,
title = "Interlinking Iconclass Data with Concepts of Art {\&} Architecture Thesaurus",
author = "Breit, Anna",
editor = "Abgaz, Yalemisew and
Dorn, Amelie and
Diaz, Jose Luis Preza and
Koch, Gerda",
booktitle = "Proceedings of the 1st International Workshop on Artificial Intelligence for Historical Image Enrichment and Access",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2020.ai4hi-1.2",
pages = "11--15",
abstract = "Iconclass, being a a well established classification system, could benefit from interconnections with other ontologies in order to semantically enrich its content. This work presents a disambiguating and interlinking approach which is used to map Iconclass Subjects to concepts of the Art and Architecture Thesaurus. In a preliminary evaluation, the system is able to produce promising predictions, though the task is highly challenging due to conceptual and schema heterogeneity. Several algorithmic improvements for this specific interlinking task, as well as and future research directions are suggestions. The produced mappings, as well as the source code and additional information can be found at \url{https://github.com/annabreit/taxonomy-interlinking}.",
language = "English",
ISBN = "979-10-95546-63-4",
}
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<abstract>Iconclass, being a a well established classification system, could benefit from interconnections with other ontologies in order to semantically enrich its content. This work presents a disambiguating and interlinking approach which is used to map Iconclass Subjects to concepts of the Art and Architecture Thesaurus. In a preliminary evaluation, the system is able to produce promising predictions, though the task is highly challenging due to conceptual and schema heterogeneity. Several algorithmic improvements for this specific interlinking task, as well as and future research directions are suggestions. The produced mappings, as well as the source code and additional information can be found at https://github.com/annabreit/taxonomy-interlinking.</abstract>
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%0 Conference Proceedings
%T Interlinking Iconclass Data with Concepts of Art & Architecture Thesaurus
%A Breit, Anna
%Y Abgaz, Yalemisew
%Y Dorn, Amelie
%Y Diaz, Jose Luis Preza
%Y Koch, Gerda
%S Proceedings of the 1st International Workshop on Artificial Intelligence for Historical Image Enrichment and Access
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-63-4
%G English
%F breit-2020-interlinking
%X Iconclass, being a a well established classification system, could benefit from interconnections with other ontologies in order to semantically enrich its content. This work presents a disambiguating and interlinking approach which is used to map Iconclass Subjects to concepts of the Art and Architecture Thesaurus. In a preliminary evaluation, the system is able to produce promising predictions, though the task is highly challenging due to conceptual and schema heterogeneity. Several algorithmic improvements for this specific interlinking task, as well as and future research directions are suggestions. The produced mappings, as well as the source code and additional information can be found at https://github.com/annabreit/taxonomy-interlinking.
%U https://aclanthology.org/2020.ai4hi-1.2
%P 11-15
Markdown (Informal)
[Interlinking Iconclass Data with Concepts of Art & Architecture Thesaurus](https://aclanthology.org/2020.ai4hi-1.2) (Breit, AI4HI 2020)
ACL