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Measuring similarity for fusing extracted knowledge
Andriy Nikolov, Dr. Victoria Uren, Prof. Enrico Motta, Prof. Anne de Roeck This event took place on 9th March 2006 at 9:00am (09:00 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA
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In order to use semantically annotated data from the Web it is necessary to integrate information retrieved from different sources. This process is called knowledge fusion. The information retrieved from the Web can be inconsistent, incomplete and unreliable. Because of this sometimes it can be hard to determine whether two instances represent the same real-world entity or not. Any fusion algorithm should be able to deal with these inconsistencies. This paper describes an algorithm to deal with the instance integration problem and proposes a set of experiments needed to evaluate its performance using the TAP ontology.
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