Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Learning to classify structured data by graph propositionalization
KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
2006 (English)In: Proc. IASTED Int. Conf. Comput. Intell., CI, 2006, 393-398 p.Conference paper, Published paper (Refereed)
Abstract [en]

Existing methods for learning from structured data are limited with respect to handling large or isolated substructures and also impose constraints on search depth and induced structure length. An approach to learning from structured data using a graph based propositionalization method, called finger printing, is introduced that addresses the limitations of current methods. The method is implemented in a system called DIFFER, which is demonstrated to compare favorable to existing state-of-art methods on some benchmark data sets. It is shown that further improvements can be obtained by combining the features generated by finger printing with features generated by previous methods.

Place, publisher, year, edition, pages
2006. 393-398 p.
Series
Proceedings of the 2nd IASTED International Conference on Computational Intelligence, CI 2006
Keyword [en]
Classification, Graph, Machine learning, Structured data, Artificial intelligence, Education, Graph theory, Intelligent control, Learning systems, Printing, Art methods, Benchmark datums, Existing methods, Finger printings, Graph based, Induced structures, Propositionalization, Structured datums, Sub structures, Computational geometry
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-155345ISI: 000243777100069Scopus ID: 2-s2.0-56349162143ISBN: 0889866023 (print)ISBN: 9780889866027 (print)OAI: oai:DiVA.org:kth-155345DiVA: diva2:763705
Conference
2nd IASTED International Conference on Computational Intelligence, CI 2006, 20-22 November 2006, San Francisco, CA, USA
Note

QC 20141117

Available from: 2014-11-17 Created: 2014-11-05 Last updated: 2016-12-19Bibliographically approved

Open Access in DiVA

No full text

Scopus

Search in DiVA

By author/editor
Karunaratne, ThashmeeBoström, Henrik
By organisation
Computer and Systems Sciences, DSV
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 6 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf