@inbook{5c8046aa6f4542cfaf255e4fcc6c590c,
  title     = "Matching unstructured vocabularies using a background ontology",
  abstract  = "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.",
  author    = "Zharko Aleksovski and Michel Klein and {Ten Kate}, Warner and {Van Harmelen}, Frank",
  year      = "2006",
  doi       = "10.1007/11891451_18",
  isbn      = "3540463631",
  volume    = "4248 LNAI",
  series    = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  publisher = "Springer/Verlag",
  pages     = "182--197",
  booktitle = "Managing Knowledge in a World of Networks - 15th International Conference, EKAW 2006, Proceedings",
}

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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. 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