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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentifierQABCDSTQQW/46B5A55
Repositoryurlib.net/www/2022/02.08.11.29   (restricted access)
Last Update2022:02.08.11.29.49 (UTC) simone
Metadata Repositoryurlib.net/www/2022/02.08.11.29.49
Metadata Last Update2022:04.03.23.14.43 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1109/CLEI53233.2021.9639968
ISBN978-166549503-5
Citation KeySantosSSFWCMAV:2021:ExSyMa
TitleUsing Open Information Extraction to Extract Relations: An Extended Systematic Mapping
Year2021
Access Date2024, June 15
Secondary TypePRE CI
Number of Files1
Size1558 KiB
2. Context
Author1 Santos, Vinícius dos
2 Silva, Patrick R.
3 Souza, Érica F. de
4 Felizardo, Katia R.
5 Watanabe, Willian M.
6 Cândido Júnior, Arnaldo
7 Meinerz, Giovani V.
8 Aluísio, Sandra M.
9 Vijaykumar, Nandamudi Lankalapalli
Resume Identifier1
2
3
4
5
6
7
8
9 8JMKD3MGP5W/3C9JHTU
Group1
2
3
4
5
6
7
8
9 COPDT-CGIP-INPE-MCTI-GOV-BR
Affiliation1 Universidade de São Paulo (USP)
2 Universidade Tecnológica Federal do Paraná (UTFPR)
3 Universidade Tecnológica Federal do Paraná (UTFPR)
4 Universidade Tecnológica Federal do Paraná (UTFPR)
5 Universidade Tecnológica Federal do Paraná (UTFPR)
6 Universidade Tecnológica Federal do Paraná (UTFPR)
7 Universidade Tecnológica Federal do Paraná (UTFPR)
8 Universidade de São Paulo (USP)
9 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 vinicius.dos.santos@usp.br
2 patrick.1985@alunos.utfpr.edu.br
3 ericasouza@utfpr.edu.br
4 katiascannavino@utfpr.edu.br
5 wwatanabe@utfpr.edu.br
6 arnaldoc@utfpr.edu.br
7 giovanimeinerz@utfpr.edu.br
8 sandra@icmc.usp.br
9 vijaykumar.nandamudi@gmail.com
Conference NameLatin American Computing Conference, 47
Conference LocationOnline
Date25-29 Oct. 2021
PublisherIEEE
Book TitleProceedings
History (UTC)2022-02-08 11:30:43 :: simone -> administrator :: 2021
2022-04-03 23:14:43 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractContext: For thousands of years humans have been using natural language to register their knowledge on important information to enable its access to future generations. With internet, a large amount of textual data is produced and shared on a daily basis. So, scientists started to research techniques for efficiently process knowledge stored in textual format. In this context, Natural Language Processing (NLP) became a popular area studying linguistic phenomena and using computational methods to process texts in natural language. In particular, Open Information Extraction (Open IE) was proposed to gather information from plain text. Despite the advances in this area, it is still necessary to map details about how these approaches were proposed to support the community while creating more efficient Open IE systems. Objective: In this paper, we identify, in the literature, the main characteristics of proposed Open IE approaches. Method: First, we extended the search performed in a systematic mapping previously published by using backward snowballing and a manual search. Next, we updated the electronic database search including ACL Anthology. Finally, 159 studies proposing Open IE approaches were considered for data extraction. Results: Data analysis showed a significant increase in the number of studies published about Open IE in the last years. In addition, we provide important details about how these techniques were proposed (e.g., data sets used and output evaluation techniques). Results indicate that researchers started to adopt neural networks to perform Open IE instead of using conventional supervised learning techniques. Conclusion: Recent advances in Artificial Intelligence and neural networks techniques allowed scientists to have a new perspective on how to perform efficient textual data management. Therefore, Open IE approaches gained much attention as they can help in many contexts, especially in knowledge management tasks.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > Using Open Information...
doc Directory Contentaccess
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4. Conditions of access and use
Languageen
Target FileSantos_2021_using.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2021/06.04.03.40.25
Next Higher Units8JMKD3MGPCW/46KUES5
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.56.50 2
sid.inpe.br/bibdigital/2022/04.03.23.11 1
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor format issn keywords label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url volume
7. Description control
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