Evolutionary algorithm based on different semantic similarity functions for synonym recognition in the biomedical domain
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by
Lectures Hagenberg
2018
Abstract
One of the most challenging problems in the semantic web field consists
of computing the semantic similarity between different terms. The
problem here is the lack of accurate domain-specific dictionaries, such
as biomedical, financial or any other particular and dynamic field. In
this article we propose a new approach which uses different existing
semantic similarity methods to obtain precise results in the biomedical
domain. Specifically, we have developed an evolutionary algorithm which
uses information provided by different semantic similarity metrics. Our
results have been validated against a variety of biomedical datasets and
different collections of similarity functions. The proposed system
provides very high quality results when compared against similarity
ratings provided by human experts (in terms of Pearson correlation
coefficient) surpassing the results of other relevant works previously
published in the literature.
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Date 2018-07-19
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