Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources
The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relation...
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| Format: | Online |
| Langue: | anglais |
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Peter Lang International Academic Publishers
2021
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| Accès en ligne: | 1003170 |
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| _version_ | 1869522546183897088 |
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| author | Wohlgenannt, Gerhard |
| author_browse | Wohlgenannt, Gerhard |
| author_facet | Wohlgenannt, Gerhard |
| author_sort | Wohlgenannt, Gerhard |
| collection | Directory of Open Access Books |
| description | The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach. |
| format | Online |
| id | doab-20.500.12854ir-27633 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Peter Lang International Academic Publishers |
| publisherStr | Peter Lang International Academic Publishers |
| record_format | ojs |
| spelling | doab-20.500.12854ir-276332025-07-21T15:58:00Z Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources Wohlgenannt, Gerhard Based Combining Corpus Data from Learning machine learning natural language learning Ontology Reasoning relation labeling Relations Semantic Sources Techniques Wohlgenannt thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach. 2021-02-10T12:58:18Z 2019-01-10 23:55 2018-12-01 23:55:55 2020-01-14 16:18:01 2020-04-01T11:28:34Z 2018 book 1003170 OCN: 1082971313 http://library.oapen.org/handle/20.500.12657/26873 9783631753842 https://directory.doabooks.org/handle/20.500.12854/27633 eng Forschungsergebnisse der Wirtschaftsuniversitaet Wien open access image/jpeg image/jpeg image/jpeg image/jpeg image/jpeg n/a n/a n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/26873/1/1003170.pdf https://library.oapen.org/bitstream/20.500.12657/26873/1/1003170.pdf https://library.oapen.org/bitstream/20.500.12657/26873/1/1003170.pdf https://library.oapen.org/bitstream/20.500.12657/26873/1/1003170.pdf https://library.oapen.org/bitstream/20.500.12657/26873/1/1003170.pdf Peter Lang International Academic Publishers 10.3726/b13903 10.3726/b13903 44a712f0-ee17-4c08-a667-46effed595e7 9783631753842 222 Bern open access |
| spellingShingle | Based Combining Corpus Data from Learning machine learning natural language learning Ontology Reasoning relation labeling Relations Semantic Sources Techniques Wohlgenannt thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software Wohlgenannt, Gerhard Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title | Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title_full | Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title_fullStr | Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title_full_unstemmed | Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title_short | Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources |
| title_sort | learning ontology relations by combining corpus based techniques and reasoning on data from semantic web sources |
| topic | Based Combining Corpus Data from Learning machine learning natural language learning Ontology Reasoning relation labeling Relations Semantic Sources Techniques Wohlgenannt thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software |
| topic_facet | Based Combining Corpus Data from Learning machine learning natural language learning Ontology Reasoning relation labeling Relations Semantic Sources Techniques Wohlgenannt thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics::UBJ Digital and information technologies: social and ethical aspects thema EDItEUR::U Computing and Information Technology::UF Business applications::UFL Enterprise software |
| url | 1003170 |
| work_keys_str_mv | AT wohlgenanntgerhard learningontologyrelationsbycombiningcorpusbasedtechniquesandreasoningondatafromsemanticwebsources |