Using Google Distance to weight approximate ontology matches
Risto Gligorov
Zharko Aleksovski
Warner ten Kate
F. van Harmelen
Discovering mappings between concept hierarchies is widely regarded
as one of the hardest and most urgent problems facing the
Semantic Web. The problem is even harder in domains where concepts
are inherently vague and ill-defined, and cannot be given a
crisp definition. A notion of approximate concept mapping is required
in such domains, but until now, no such notion is available.
The first contribution of this paper is a definition for approximate
mappings between concepts. Roughly, a mapping between
two concepts is decomposed into a number of submappings, and a
sloppiness value determines the fraction of these submappings that
can be ignored when establishing the mapping.
A potential problem of such a definition is that with an increasing
sloppiness value, it will gradually allow mappings between any two
arbitrary concepts. To improve on this trivial behaviour, we need
to design a heuristic weighting which minimises the sloppiness required
to conclude desirable matches, but at the same time maximises
the sloppiness required to conclude undesirable matches.
The second contribution of this paper is to show that a Googlebased
similarity measure has exactly these desirable properties.
We establish these results by experimental validation in the domain
of musical genres. We show that this domain does suffer from
ill-defined concepts. We take two real-life genre hierarchies from
theWeb, we compute approximate mappings between them at varying
levels of sloppiness, and we validate our results against a handcrafted
Gold Standard.
Our method makes use of the huge amount of knowledge that is
implicit in the currentWeb, and exploits this knowledge as a heuristic
for establishing approximate mappings between ill-defined concepts.
(PDF
paper, 280Kb)
@InProceedings{WWW07,
author = "Risto Gligorov and Zharko Aleksovski and
Warner ten Kate and F. van Harmelen",
title = "Using Google Distance to weight approximate ontology matches",
booktitle = "Proceedings of the seventeenth World Wide Web conference {WWWW}'07",
year = 2007,
pages = "767-776",
address = "Korea",
month = "May",
keywords = {Semantic Web, Approximate Reasoning},
urlPaper = "http://www.cs.vu.nl/~frankh/postscript/WWW07.pdf"
}
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