Matching unstructured vocabularies using a background ontology

Zharko Aleksovski*, Michel Klein, Warner Ten Kate, Frank Van Harmelen

*Corresponding author for this work

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


Existing ontology matching algorithms use a combination of lexical and structural correspondence between source and target ontologies. We present a realistic case-study where both types of overlap are low: matching two unstructured lists of vocabulary used to describe patients at Intensive Care Units in two different hospitals. We show that indeed existing matchers fail on our data. We then discuss the use of background knowledge in ontology matching problems. In particular, we discuss the case where the source and the target ontology are of poor semantics, such as flat lists, and where the background knowledge is of rich semantics, providing extensive descriptions of the properties of the concepts involved. We evaluate our results against a Gold Standard set of matches that we obtained from human experts.

Original languageEnglish
Title of host publicationManaging Knowledge in a World of Networks - 15th International Conference, EKAW 2006, Proceedings
Number of pages16
Volume4248 LNAI
ISBN (Print)3540463631, 9783540463634
Publication statusPublished - 2006
Event15th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2006 - Podebrady, Czech Republic
Duration: 2 Oct 20066 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4248 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349


Conference15th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2006
Country/TerritoryCzech Republic


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