Probabilistic Data Integration

Maurice van Keulen

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

39 Citations (Scopus)
103 Downloads (Pure)


In data integration efforts such as in portal development, much development time is devoted to entity resolution. Often advanced similarity measurement techniques are used to remove semantic duplicates or solve other semantic conflicts. It proofs impossible, however, to automatically get rid of all semantic problems. An often-used rule of thumb states that about 90% of the development effort is devoted to semi-automatically resolving the remaining 10% hard cases. In an attempt to significantly decrease human effort at data integration time, we have proposed an approach that strives for a 'good enough' initial integration which stores any remaining semantic uncertainty and conflicts in a probabilistic XML database. The remaining cases are to be resolved during use with user feedback. We conducted extensive experiments on the effects and sensitivity of rule denition, threshold tuning, and user feedback on the integration quality. We claim that our approach indeed reduces development effort - and not merely shifts the effort - by showing that setting rough safe thresholds and defining only a few rules suffices to produce a 'good enough' integration that can be meaningfully used, and that user feedback is effective in gradually improving the integration quality.
Original languageEnglish
Title of host publication08421 Abstracts Collection - Uncertainty Management in Information Systems
EditorsChristoph Koch, Birgitta König-Ries, Volker Markl, Maurice van Keulen
Place of PublicationDagstuhl, Germany
Number of pages1
Publication statusPublished - Mar 2009
EventUncertainty Management in Information Systems: Dagstuhl Seminar 08421 - Dagstuhl, Germany, Dagstuhl, Germany
Duration: 12 Oct 200817 Oct 2008

Publication series

NameDagstuhl Seminar Proceedings
PublisherSchloss Dagstuhl - Leibniz-Zentrum fuer Informatik
ISSN (Print)1862-4405


WorkshopUncertainty Management in Information Systems
Other12 - 17 Oct 2008


  • probabilistic databases
  • EWI-15237
  • Uncertainty management
  • METIS-265199
  • data quality
  • IR-65438
  • Data Integration
  • entity resolution


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