Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/47RJ2EE
Repositorysid.inpe.br/sibgrapi/2022/10.21.13.32
Last Update2022:10.21.13.32.48 (UTC) viniciusrpb@unb.br
Metadata Repositorysid.inpe.br/sibgrapi/2022/10.21.13.32.48
Metadata Last Update2023:05.23.04.20.43 (UTC) administrator
Citation KeyHolandaRomBotZanBor:2022:FoDaAn
TitleFood Data Analysis using Multidimensional Visualizations based on Point Placement
FormatOn-line
Year2022
Access Date2024, May 01
Number of Files1
Size821 KiB
2. Context
Author1 Holanda, Maria Eduarda M. de
2 Romão, Bernardo
3 Botelho, Raquel Braz Assunção
4 Zandonadi, Renata Puppin
5 Borges, Vinícius R. P.
Affiliation1 Universidade de Brasília
2 Universidade de Brasília
3 Universidade de Brasília
4 Universidade de Brasília
5 Universidade de Brasília
e-Mail Addresseduarda.holanda@aluno.unb.br
Conference NameConference on Graphics, Patterns and Images, 35 (SIBGRAPI)
Conference LocationNatal, RN
Date24-27 Oct. 2022
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2022-10-21 13:32:48 :: viniciusrpb@unb.br -> administrator ::
2023-05-23 04:20:43 :: administrator -> :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsfood composition data
data visualization
visual data mining
point placement strategies
AbstractFood data comprise records regarding nutrients, ingredients, amounts of different vitamins and minerals that can be found in foods. The wide variety of food products that can be stored in large datasets makes the traditional analysis tasks unfeasible and time-consuming when conducted manually by the dietitians and related professionals. This paper describes a method for visualizing food data using point placement strategies to support specialists in tasks related to determining similar food products that can be replaced in specific diets. The proposed method generates a structured representation for food data to be used as input to some state-of-the-art and recent visualizations, such as PCA, t-SNE, UMAP and TriMap. Experiments were conducted to assess the quality of visualizations and the results reported that the nonlinear visualizations presented satisfactory discriminability regarding some food categories and better preservation of the data patterns. A case study based on a visual exploration process was also conducted and demonstrates the specialist successfully finding substitute food products for planning a vegan diet plan.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2022 > Food Data Analysis...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 21/10/2022 10:32 1.6 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/47RJ2EE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/47RJ2EE
Languageen
Target Filewuw2022_camera_ready_correct.pdf
User Groupviniciusrpb@unb.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/495MHJ8
Citing Item Listsid.inpe.br/sibgrapi/2023/05.19.12.10 9
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition editor electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


Close