Logo des Repositoriums
 

Entity Extraction in the Ecological Domain – A practical guide

dc.contributor.authorUdovenko, Vladimir
dc.contributor.authorAlgergawy, Alsayed
dc.contributor.editorMeyer, Holger
dc.contributor.editorRitter, Norbert
dc.contributor.editorThor, Andreas
dc.contributor.editorNicklas, Daniela
dc.contributor.editorHeuer, Andreas
dc.contributor.editorKlettke, Meike
dc.date.accessioned2019-04-15T11:40:31Z
dc.date.available2019-04-15T11:40:31Z
dc.date.issued2019
dc.description.abstractScientific information comes in many shapes: As data in databases or spreadsheets, but also as textual information in papers and books. In order to exploit all this information and integrate all the knowledge that is available regarding a specific entity, it is necessary to identify entities and their relationships. In this paper, we provide a guideline to setting up a pipeline that supports entity and relationship extraction from scientific publications from the ecological domain.en
dc.identifier.doi10.18420/btw2019-ws-16
dc.identifier.isbn978-3-88579-684-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/21802
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2019 – Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) – Proceedings, Volume P-290
dc.subjectInformation integration
dc.subjectEntity extraction
dc.subjectRelation extraction
dc.titleEntity Extraction in the Ecological Domain – A practical guideen
gi.citation.endPage160
gi.citation.startPage155
gi.conference.date4.-8. März 2019
gi.conference.locationRostock
gi.conference.sessiontitleWorkshop on Big (and Small) Data in Science and Humanities (BigDS 2019)

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
C2-6.pdf
Größe:
277.14 KB
Format:
Adobe Portable Document Format