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JCR Impact Factor: 0.825
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  2/2009 - 3

Knowledge Acquisition from Historical Documents for Preserving Transylvanian Cultural Heritage

SALOMIE, I. See more information about SALOMIE, I. on SCOPUS See more information about SALOMIE, I. on IEEExplore See more information about SALOMIE, I. on Web of Science, DINSOREANU, M. See more information about  DINSOREANU, M. on SCOPUS See more information about  DINSOREANU, M. on SCOPUS See more information about DINSOREANU, M. on Web of Science, POP, C. See more information about  POP, C. on SCOPUS See more information about  POP, C. on SCOPUS See more information about POP, C. on Web of Science, SUCIU, S. See more information about SUCIU, S. on SCOPUS See more information about SUCIU, S. on SCOPUS See more information about SUCIU, S. on Web of Science
 
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Download PDF pdficon (476 KB) | Citation | Downloads: 1,148 | Views: 4,725

Author keywords
knowledge acquisition, lexical annotation, knowledge retrieval, ontology, semantic annotation

References keywords
information(6), language(4)
No common words between the references section and the paper title.

About this article
Date of Publication: 2009-06-02
Volume 9, Issue 2, Year 2009, On page(s): 16 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.02003
Web of Science Accession Number: 000268723600003
SCOPUS ID: 70349187192

Abstract
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Full text preview
This paper proposes a solution for preserving the cultural heritage by performing knowledge acquisition from historical documents. We developed a system that gathers knowledge by processing the content of historical documents to enable knowledge retrieval as response to ontologically-guided queries. Knowledge acquisition, one of the main workflows in our system, aims to semantically annotate the content of historical documents and to enrich the domain ontology through lexical annotation and knowledge extraction processes. We use two types of rules in knowledge extraction, one dealing with extracting the relevant information from the documents' content and another one for mapping the extracted information to ontology concepts and properties. Our work was validated on documents available in the Cluj County National Archives addressing the Transylvanian medieval history.


References | Cited By  «-- Click to see who has cited this paper

[1] F. Amardeilh, "Web Semantique et Informatique Linguistique: propositions methodologiques et realisation d'une plateforme logicielle". These de Doctorat, Universite Paris X-Nanterrere, 2007.

[2] F. Amardeilh, "OntoPop or how to annotate documents and populate ontologies from texts". ESWC'06 Proceedings of the Workshop on Mastering the Gap: From Information Extraction to Semantic Representation, 2006

[3] P. Buitelaar, P. Cimiano, S. Racioppa, M. Siegel, "Ontology-based Information Extraction with SOBA", Proceedings of the International Conference on Language Resources and Evaluation, pp. 2321-2324, 2006

[4] M. Laclavik, M. Ciglan, M. Seleng, S. Krajei: "Ontea, "Semi-automatic Pattern based Text Annotation empowered with Information Retrieval Methods". In Tools for acquisition, organisation and presenting of information and knowledge: proceedings in Informatics and Information Technologies, ISBN 978-80-227-2716-7, part 2, pp. 119-129, Kosice, Vydavatelstvo STU, Bratislava, 2006

[5] M. Laclavik, M. Seleng, M. Babik, "OnTeA: Semi-automatic Ontology based Text Annotation Method". In Tools for Acquisition, Organisation and Presenting of Information and Knowledge, ISBN 80-227-2468-8, pp. 49-63, Vydavatelstvo STU, Bratislava, 2006

[6] U. Schafer, "Integrating Deep and Shallow Natural Language Processing Components - Representations and Hybrid Architectures". Saarbrucken Dissertations in Computational Linguistics and Language Te, DFKI GmbH and Computational Linguistics Department, Saarland University, Saarbrucken, Germany, 2007

[7] V. Tablan, D. Maynard, K. Bontcheva, H. Cunningham, "Gate - An Application Developer's Guide", Available online: http://gate.ac.uk, 2004

[8] Jess the Rule Engine for the Java Platform, Version 7.1, Available online: http://www.jessrules.com/jess/docs/Jess71.pdf, 2008

[9] I. Horrocks et al., "SWRL: A Semantic Web Rule Language Combining OWL and RuleML". Available online: http://www.w3.org/Submission/SWRL, 2004

[10] M. Horridge, et al, "A Practical Guide To Building OWL Ontologies Using Protege 4 and CO-ODE Tools". Available online: http://owl.cs.manchester.ac.uk/-tutorials/protegeowltutorial

[11] O. Matei, "Ontology-based knowledge organization for the radiograph images segmentation", Advances in Electrical and Computer Engineering, vol. 8, no. 1, 2008, pp. 56-61
[CrossRef] [Full Text] [Web of Science Times Cited 7] [SCOPUS Times Cited 9]


[12] CCNA, Cluj County National Archives, Available online: http://www.clujnapoca.ro/arhivelenationale

References Weight

Web of Science® Citations for all references: 7 TCR
SCOPUS® Citations for all references: 9 TCR

Web of Science® Average Citations per reference: 1 ACR
SCOPUS® Average Citations per reference: 1 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2022-06-30 21:51 in 12 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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