Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Incremental causal discovery and visualization
RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.ORCID-id: 0000-0001-8577-6745
Halmstad University, Sweden .ORCID-id: 0000-0003-3272-4145
University of Skövde, Sweden .
2019 (engelsk)Inngår i: Proceedings of the Workshop on Interactive Data Mining, WIDM 2019, Association for Computing Machinery, Inc , 2019Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Discovering causal relations from limited amounts of data can be useful for many applications. However, all causal discovery algorithms need huge amounts of data to estimate the underlying causal graph. To alleviate this gap, this paper proposes a novel visualization tool which incrementally discovers causal relations as more data becomes available. That is, we assume that stronger causal links will be detected quickly and weaker links revealed when enough data is available. In addition to causal links, the correlation between variables and the uncertainty of the strength of causal links are visualized in the same graph. The tool is illustrated on three example causal graphs, and results show that incremental discovery works and that the causal structure converges as more data becomes available. © 2019 Copyright held by the owner/author(s).

sted, utgiver, år, opplag, sider
Association for Computing Machinery, Inc , 2019.
Emneord [en]
Causal Discovery, Correlation, Incremental Visualization, Correlation methods, Data mining, Visualization, Causal graph, Causal relations, Discovery algorithm, Incremental discoveries, Novel visualizations, Data visualization
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-39672DOI: 10.1145/3304079.3310287Scopus ID: 2-s2.0-85069768142ISBN: 9781450362962 (tryckt)OAI: oai:DiVA.org:ri-39672DiVA, id: diva2:1341124
Konferanse
1st Workshop on Interactive Data Mining, WIDM 2019, co-located with 12th ACM International Conference on Web Search and Data Mining, WSDM 2019, 15 February 2019
Merknad

Funding text 1: This research has been conducted within the “A Big Data Analytics Framework for a Smart Society" (BIDAF) project supported by the Swedish Knowledge Foundation.

Tilgjengelig fra: 2019-08-07 Laget: 2019-08-07 Sist oppdatert: 2023-11-06bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstScopus

Person

Holst, AndersPashami, Sepideh

Søk i DiVA

Av forfatter/redaktør
Holst, AndersPashami, Sepideh
Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 64 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
v. 2.43.0