A Demonstration System towards NLP and Knowledge Driven Data Platforms for Civil Engineering
| dc.contributor.author | Borst,Janos | |
| dc.contributor.author | Meinecke,Christofer | |
| dc.contributor.author | Wiegreffe,Daniel | |
| dc.contributor.author | Niekler,Andreas | |
| dc.contributor.editor | Demmler, Daniel | |
| dc.contributor.editor | Krupka, Daniel | |
| dc.contributor.editor | Federrath, Hannes | |
| dc.date.accessioned | 2022-09-28T17:10:20Z | |
| dc.date.available | 2022-09-28T17:10:20Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | We present a demonstrator that shows a concept towards a smart document platform for Civil Engineering. It demonstrates NLP-supported organisation of documents included into a graphical user interface. The demonstrator addresses the fundamental problem of data structure that includes the internal project logic of a planning project in Civil Engineering. To this end, we build a knowledge graph that includes not only domain-specific knowledge but also standardised project structures. So far included functionalities are a navigation that allows filtering according to a logic familiar to engineers and a simplified data import via automatic classification and tagging using language technologies. | en |
| dc.identifier.doi | 10.18420/inf2022_25 | |
| dc.identifier.isbn | 978-3-88579-720-3 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/39523 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | INFORMATIK 2022 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-326 | |
| dc.subject | NLP | |
| dc.subject | Knowledge Graphs | |
| dc.subject | Artificial Intelligence | |
| dc.title | A Demonstration System towards NLP and Knowledge Driven Data Platforms for Civil Engineering | en |
| gi.citation.endPage | 282 | |
| gi.citation.startPage | 271 | |
| gi.conference.date | 26.-30. September 2022 | |
| gi.conference.location | Hamburg | |
| gi.conference.sessiontitle | Künstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2022) |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- kikmu_03.pdf
- Größe:
- 460.5 KB
- Format:
- Adobe Portable Document Format