Logo des Repositoriums
 

Textual Case-based Adaptation using Semantic Relatedness - A Case Study in the Domain of Security Documents

dc.contributor.authorKorger, Andreas
dc.contributor.authorBaumeister, Joachim
dc.contributor.editorHeisig, Peter
dc.contributor.editorOrth, Ronald
dc.contributor.editorSchönborn, Jakob Michael
dc.contributor.editorThalmann, Stefan
dc.date.accessioned2020-10-05T11:30:37Z
dc.date.available2020-10-05T11:30:37Z
dc.date.issued2020
dc.description.abstractIn previous efforts graph-based and textual knowledge representations were combined for the usage in case-based reasoning. This work proposes first steps for this combination in the domain of secu- rity documents and similar document classes. We present an approach pre-processing documents for textual case-based reasoning by adapting methods of natural language processing. We propose a method improving a case-based hierarchical similarity assessment for retrieval by introducing the concept of vector space embeddings and semantic relatedness of words and phrases.en
dc.identifier.isbn978-3-88579-607-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34390
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofWM 2019 - Wissensmanagement in digitalen Arbeitswelten: Aktuelle Ansätze und Perspektiven - Knowledge Management in Digital Workplace Environments: State of the Art and Outlook
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-303
dc.subjectCase-based reasoning · Textual similarity · Textual case- based reasoning · Vector space embeddings · Semantic relatedness · Graph- based knowledge
dc.titleTextual Case-based Adaptation using Semantic Relatedness - A Case Study in the Domain of Security Documentsen
dc.typeText/Conference Paper
gi.citation.endPage122
gi.citation.publisherPlaceBonn
gi.citation.startPage108
gi.conference.date18.-20. März 2019
gi.conference.locationPotsdam
gi.conference.sessiontitleWS III: 8th German Workshop on Experience Management

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
WM2019-108-122.pdf
Größe:
962.92 KB
Format:
Adobe Portable Document Format