Exploiting relation extraction for ontology alignment
|Exploiting relation extraction for ontology alignment|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Ontology Alignment, Relation Extraction, Wikipedia (Extra: Application systems, Background knowledge, Extraction techniques, Ontology alignment, Ontology design, Relation extraction, Semantic navigation, Semantic relations, Similarity measure, Text corpora, Wikipedia, Alignment, Semantic Web, Semantics, Ontology)|
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Exploiting relation extraction for ontology alignment is a 2010 conference paper written in English by Beisswanger E. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
When multiple ontologies are used within one application system, aligning the ontologies is a prerequisite for interoperability and unhampered semantic navigation and search. Various methods have been proposed to compute mappings between elements from different ontologies, the majority of which being based on various kinds of similarity measures. As a major shortcoming of these methods it is difficult to decode the semantics of the results achieved. In addition, in many cases they miss important mappings due to poorly developed ontology structures or dissimilar ontology designs. I propose a complementary approach making massive use of relation extraction techniques applied to broad-coverage text corpora. This approach is able to detect different types of semantic relations, dependent on the extraction techniques used. Furthermore, exploiting external background knowledge, it can detect relations even without clear evidence in the input ontologies themselves.
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