Activity matching with human intelligence

Carlos RodríGuez*, Christopher Klinkmüller, Ingo Weber, Florian Daniel, Fabio Casati

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

11 Citations (Scopus)


Effective matching of activities is the first step toward successful process model matching and search. The problem is nontrivial and has led to a variety of computational similarity metrics and matching approaches, however all still with low performance in terms of precision and recall. In this paper, instead, we study how to leverage on human intelligence to identify matches among activities and show that the problem is not as straightforward as most computational approaches assume. We access human intelligence (i) by crowdsourcing the activity matching problem to generic workers and (ii) by eliciting ground truth matches from experts. The precision and recall we achieve and the qualitative analysis of the results testify huge potential for a human-based activity matching that contemplates disagreement and interpretation.

Original languageEnglish
Title of host publicationBusiness Process Management Forum
Subtitle of host publicationBPM Forum 2016, Rio de Janeiro, Brazil, September 18–22, 2016, proceedings
EditorsMarcello La Rosa, Peter Loos, Oscar Pastor
Place of PublicationCham
PublisherSpringer, Springer Nature
Number of pages17
ISBN (Electronic)9783319454689
ISBN (Print)9783319454672
Publication statusPublished - 2016
EventInternational Conference on Business Process Management, BPM 2016 - Rio de Janeiro, Brazil
Duration: 18 Sept 201622 Sept 2016

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356


OtherInternational Conference on Business Process Management, BPM 2016
CityRio de Janeiro


  • Activity matching
  • Crowdsourcing
  • Label matching


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