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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M9H4AE
Repositorysid.inpe.br/sibgrapi/2016/08.15.22.59
Last Update2016:08.15.22.59.08 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/08.15.22.59.08
Metadata Last Update2022:05.18.22.21.07 (UTC) administrator
Citation KeyBertonLope:2016:NeCoAp
TitleNetwork Construction and Applications for Semi-Supervised Learning
FormatOn-line
Year2016
Access Date2024, Apr. 28
Number of Files1
Size903 KiB
2. Context
Author1 Berton, Lilian
2 Lopes, Alneu de Andrade
Affiliation1 Universidade do Estado de Santa Catarina
2 Universidade de São Paulo
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addresslilian.2as@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2016-08-15 22:59:08 :: lilian.2as@gmail.com -> administrator ::
2022-05-18 22:21:07 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsnetwork construction
graph-based methods
semi-supervised learning
complex networks
AbstractThe influence of network construction on graph-based semi-supervised learning (SSL) and their related applications have only received limited study despite its critical impact on accuracy. We introduce four variants for networkconstruction for SSL that adopt different network topology: 1) S-kNN (Sequential k-Nearest Neighbors) that generates regular networks; 2) GBILI (Graph Based on the informativeness of Labeled Instances) and 3) RGCLI (Robust Graph that Considers Labeled Instances), which exploit the labels available generating scale-free networks; 4) GBLP (Graph Based on Link Prediction), which are based on link prediction measures and creates smallworld networks. Comprehensive experimental results using several benchmark datasets show that it can achieve or outperform existing state-of-the-art results. Furthermore, it is confirmed to be more effective in running time.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > Network Construction and...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M9H4AE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M9H4AE
Languageen
Target FileWTD-SIBGRAPI2016-LilianBerton-2.pdf
User Grouplilian.2as@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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