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
Using background knowledge for graph based learning: a case study in chemoinformatics
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.
2007 (English)In: IMECS 2007: International Multiconference of Engineers and Computer Scientists, Vols I and II, HONG KONG: INT ASSOC ENGINEERS-IAENG , 2007, 153-157 p.Conference paper, Published paper (Refereed)
Abstract [en]

Incorporating background knowledge in the learning process is proven beneficial for numerous applications of logic based learning methods. Yet the effect of background knowledge in graph based learning is not systematically explored. This paper describes and demonstrates the first step in this direction and elaborates on how additional relevant background knowledge could be used to improve the predictive performance of a graph learner. A case study in chemoinformatics is undertaken in this regard in which various types of background knowledge are encoded in graphs that are given as input to a graph learner. It is shown that the type of background knowledge encoded indeed has an effect on the predictive performance, and it is concluded that encoding appropriate background knowledge can be more important than the choice of the graph learning algorithm.

Place, publisher, year, edition, pages
HONG KONG: INT ASSOC ENGINEERS-IAENG , 2007. 153-157 p.
Series
Lecture Notes in Engineering and Computer Science, ISSN 2078-0958
Keyword [en]
graph propositionalization, machine learning, structured data
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-39392ISI: 000246800600028Scopus ID: 2-s2.0-84888342422ISBN: 978-988-98671-4-0 (print)OAI: oai:DiVA.org:kth-39392DiVA: diva2:440689
Conference
International Multiconference of Engineers and Computer Scientists. Kowloon, PEOPLES R CHINA. MAR 21-23, 2007
Note

QC 20110913

Available from: 2011-09-13 Created: 2011-09-09 Last updated: 2016-12-19Bibliographically approved

Open Access in DiVA

No full text

Other links

ScopusFulltext i DiVA (SUB)

Search in DiVA

By author/editor
Karunaratne, ThashmeeBoström, Henrik
By organisation
Computer and Systems Sciences, DSV
Electrical Engineering, Electronic Engineering, Information EngineeringComputer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 36 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