Text encoding and ontology—enlarging an ontology by semi-automatic generated instances.
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| Title: | Text encoding and ontology—enlarging an ontology by semi-automatic generated instances. |
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| Authors: | Zöllner-Weber, Amélie1 amelie.zoellnerweber@gmail.com |
| Source: | Literary & Linguistic Computing. Sep2011, Vol. 26 Issue 3, p365-370. 6p. 1 Color Photograph, 3 Diagrams. |
| Subjects: | Text Encoding Initiative (Document type definition), Ontology, Computer systems, Application software, Mental representation |
| Abstract: | The challenge in literary computing is (1) to model texts, to produce digital editions and (2) to model the meaning of literary phenomena which readers have in their mind when reading a text. Recently, an approach was proposed to describe and present structure and attributes of literary characters (i.e. the mental representation in a reader’s mind), to explore, and to compare different representations using an ontology. In order to expand the ontology for literary characters, users must manually extract information about characters from literary texts and, again manually, add them to the ontology. In this contribution, I present an application that supports users when working with ontologies in literary studies. Therefore, semi-automatic suggestions for including information in an ontology are generated. The challenge of my approach is to encode aspects of literary characters in a text and to fit it automatically to the ontology of literary characters. The application has been tested by using an extract of the novel ‘Melmoth the Wanderer’ (1820), written by Charles Robert Maturin. For the main character, Melmoth, 72 instances were generated and assigned successfully to the ontology. In conclusion, I think that this approach is not limited to the theme of character descriptions; it can also be adapted to other topics in literary computing and Digital Humanities. [ABSTRACT FROM AUTHOR] |
| Copyright of Literary & Linguistic Computing is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 64854177 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Text encoding and ontology—enlarging an ontology by semi-automatic generated instances. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zöllner-Weber%2C+Amélie%22">Zöllner-Weber, Amélie</searchLink><relatesTo>1</relatesTo><i> amelie.zoellnerweber@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Literary+%26+Linguistic+Computing%22">Literary & Linguistic Computing</searchLink>. Sep2011, Vol. 26 Issue 3, p365-370. 6p. 1 Color Photograph, 3 Diagrams. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Text+Encoding+Initiative+%28Document+type+definition%29%22">Text Encoding Initiative (Document type definition)</searchLink><br /><searchLink fieldCode="DE" term="%22Ontology%22">Ontology</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software%22">Application software</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+representation%22">Mental representation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The challenge in literary computing is (1) to model texts, to produce digital editions and (2) to model the meaning of literary phenomena which readers have in their mind when reading a text. Recently, an approach was proposed to describe and present structure and attributes of literary characters (i.e. the mental representation in a reader’s mind), to explore, and to compare different representations using an ontology. In order to expand the ontology for literary characters, users must manually extract information about characters from literary texts and, again manually, add them to the ontology. In this contribution, I present an application that supports users when working with ontologies in literary studies. Therefore, semi-automatic suggestions for including information in an ontology are generated. The challenge of my approach is to encode aspects of literary characters in a text and to fit it automatically to the ontology of literary characters. The application has been tested by using an extract of the novel ‘Melmoth the Wanderer’ (1820), written by Charles Robert Maturin. For the main character, Melmoth, 72 instances were generated and assigned successfully to the ontology. In conclusion, I think that this approach is not limited to the theme of character descriptions; it can also be adapted to other topics in literary computing and Digital Humanities. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Literary & Linguistic Computing is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/llc/fqr021 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 365 Subjects: – SubjectFull: Text Encoding Initiative (Document type definition) Type: general – SubjectFull: Ontology Type: general – SubjectFull: Computer systems Type: general – SubjectFull: Application software Type: general – SubjectFull: Mental representation Type: general Titles: – TitleFull: Text encoding and ontology—enlarging an ontology by semi-automatic generated instances. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zöllner-Weber, Amélie IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 02681145 Numbering: – Type: volume Value: 26 – Type: issue Value: 3 Titles: – TitleFull: Literary & Linguistic Computing Type: main |
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