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Learning to Classify Structured Data by Graph Propositionalization
Stockholms universitet, Institutionen för data- och systemvetenskap.
Stockholms universitet, Institutionen för data- och systemvetenskap.
2006 (English)In: Proceedings of the Second IASTED International Conference on Computational Intelligence, 2006Conference 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.
Keyword [en]
Machine Learning, Graph, Classification, Structured data
National Category
Computer Sciences
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:kth:diva-221564ISI: 000243777100069Scopus ID: 2-s2.0-56349162143OAI: oai:DiVA.org:kth-221564DiVA, id: diva2:1175240
Conference
The IASTED International Conference on Computational Intelligence, November 20 – 22, 2006, San Francisco, USA
Note

QC 20180209

Available from: 2018-01-17 Created: 2018-01-17 Last updated: 2018-02-09Bibliographically approved

Open Access in DiVA

fulltext(325 kB)5 downloads
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c165b7ac98be1b5ae5afe7b7754961bb6fcf26965ab62ab4339ce82fca0fff85a2b64bce23667dc9b3b3ada4edc5e98606bb30e21afcdd72cb5afa65d91def1f
Type fulltextMimetype application/pdf

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Scopushttp://www.actapress.com/Abstract.aspx?paperId=29106

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Boström, Henrik
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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