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Combining word embeddings as a tool for subject identification

Hamm, Andreas (2021) Combining word embeddings as a tool for subject identification. In: Wissensaustauschworkshop "Maschinelles Lernen VII". Wissensaustauschworkshop "Maschinelles Lernen VII", 11.-13.10.2021, Köln. (Unpublished)

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Abstract

This talk shows ungoing work aiming at finding subject matter relations between text documents and word clouds. A number of increasingly successful semantic word embedding procedures - learning semantic relations from contextual distributions - have been developed in recent years. We are interested in using these embeddings for mapping documents to subjects without having to resort to supervised training of classifiers. In order to improve the quality of such a mapping it seems necessary to combine several embedding strategies. Some approaches in this direction are presented.

Item URL in elib:https://elib.dlr.de/147623/
Document Type:Conference or Workshop Item (Speech)
Title:Combining word embeddings as a tool for subject identification
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hamm, AndreasAndreas.Hamm (at) dlr.dehttps://orcid.org/0000-0001-5854-851X
Date:12 October 2021
Journal or Publication Title:Wissensaustauschworkshop "Maschinelles Lernen VII"
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Unpublished
Keywords:Text Mining, Information Extraction, Word Embeddings
Event Title:Wissensaustauschworkshop "Maschinelles Lernen VII"
Event Location:Köln
Event Type:Workshop
Event Dates:11.-13.10.2021
Organizer:DLR
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology > Intelligent and Distributed Systems
Institute for Software Technology
Deposited By: Hamm, Andreas
Deposited On:16 Dec 2021 08:04
Last Modified:16 Dec 2021 08:04

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