Machine learning for production of Dewey Decimal
| dc.audience | Audience::Classification and Indexing Section | |
| dc.conference.sessionType | Subject Analysis and Access | |
| dc.conference.venue | Kuala Lumpur Convention Centre | |
| dc.congressWLIC | IFLA WLIC 2018 - Wrocław, Poland | |
| dc.contributor.author | Brygfjeld, Svein Arne | |
| dc.contributor.author | Wetjen, Freddy | |
| dc.contributor.author | Walsøe, André | |
| dc.date.accessioned | 2025-09-24T09:07:41Z | |
| dc.date.available | 2025-09-24T09:07:41Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Based on Open Source software and existing metadata and content, the National Library of Norway has carried out a series of experiments to study automatic classification of articles based on the Dewey Decimal Classification system. Various platforms and models for machine learning has been used. The results indicate machine learning is a suitable environment for semi-automated or fully automated production of DDC. Furthermore, they show that training of machine learning platforms may be enforced by using artificial documents. | en |
| dc.identifier.relatedurl | https://2018.ifla.org/ | |
| dc.identifier.uri | https://repository.ifla.org/handle/20.500.14598/6364 | |
| dc.language.iso | eng | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.accessRights | open access | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.keyword | Machine Learning | |
| dc.subject.keyword | Dewey Decimal Classification | |
| dc.subject.keyword | Automatic classification | |
| dc.title | Machine learning for production of Dewey Decimal | en |
| dc.type | Article | |
| ifla.Unit | Section:Classification and Indexing Section | |
| ifla.oPubId | https://library.ifla.org/id/eprint/2216/ |
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