Adaptation of NLP Techniques to Cultural Heritage Research and Documentation
Guenther Goerz
orcid.org/0000-0001-7769-3050
; Department of Computer Science, University of Erlangen-Nuremberg, Erlangen, Germany
Martin Scholz
; Department of Computer Science, University of Erlangen-Nuremberg, Erlangen, Germany
APA 6th Edition Goerz, G. i Scholz, M. (2010). Adaptation of NLP Techniques to Cultural Heritage Research and Documentation. Journal of computing and information technology, 18 (4), 317-324. https://doi.org/10.2498/cit.1001918
MLA 8th Edition Goerz, Guenther i Martin Scholz. "Adaptation of NLP Techniques to Cultural Heritage Research and Documentation." Journal of computing and information technology, vol. 18, br. 4, 2010, str. 317-324. https://doi.org/10.2498/cit.1001918. Citirano 19.01.2021.
Chicago 17th Edition Goerz, Guenther i Martin Scholz. "Adaptation of NLP Techniques to Cultural Heritage Research and Documentation." Journal of computing and information technology 18, br. 4 (2010): 317-324. https://doi.org/10.2498/cit.1001918
Harvard Goerz, G., i Scholz, M. (2010). 'Adaptation of NLP Techniques to Cultural Heritage Research and Documentation', Journal of computing and information technology, 18(4), str. 317-324. https://doi.org/10.2498/cit.1001918
Vancouver Goerz G, Scholz M. Adaptation of NLP Techniques to Cultural Heritage Research and Documentation. Journal of computing and information technology [Internet]. 2010 [pristupljeno 19.01.2021.];18(4):317-324. https://doi.org/10.2498/cit.1001918
IEEE G. Goerz i M. Scholz, "Adaptation of NLP Techniques to Cultural Heritage Research and Documentation", Journal of computing and information technology, vol.18, br. 4, str. 317-324, 2010. [Online]. https://doi.org/10.2498/cit.1001918
Sažetak The WissKI system provides a framework for ontology based science communication and cultural heritage documentation. In many cases, the documentation consists of semi-structured data records with free text fields. Most references in the texts comprise of person and place
names, as well as time specifications. We present the WissKI tools for semantic annotation using controlled vocabularies and formal ontologies derived from CIDOC Conceptual Reference Model (CRM). Current research deals with the annotations as building blocks for event recognition. Finally, we outline how the CRM helps to build bridges between documentation in different scientific disciplines.