Improving similarity measures of relatedness proximity: Toward augmented concept maps

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Decision makers relying on web search engines in concept mapping for decision support are confronted with limitations inherent in similarity measures of relatedness proximity between concept pairs. To cope with this challenge, this paper presents research model for augmenting concept maps on the basis of a novel method of co-word analysis that utilizes webometrics web counts for improving similarity measures. Technology assessment serves as a use case to demonstrate and validate our approach for a spectrum of information technologies. Results show that the yielded technology assessments are highly correlated with subjective expert assessments (n = 136; r>. 0.879), suggesting that it is safe to generalize the research model to other applications. The contribution of this work is emphasized by the current growing attention to big data.

Original languageEnglish
Pages (from-to)618-628
Number of pages11
JournalJournal of Informetrics
Issue number3
StatePublished - 1 Jul 2015


  • Augmented concept map
  • Co-word analysis
  • Relatedness proximity
  • Technology assessment
  • Webometrics

ASJC Scopus subject areas

  • Computer Science Applications
  • Library and Information Sciences


Dive into the research topics of 'Improving similarity measures of relatedness proximity: Toward augmented concept maps'. Together they form a unique fingerprint.

Cite this