Aligning Large SKOS-Like Vocabularies: Two Case Studies

In this paper we build on our methodology for combining and selecting alignment techniques for vocabularies, with two alignment case studies of large vocabularies in two languages. Firstly, we analyze the vocabularies and based on that analysis choose our alignment techniques. Secondly, we test our hypothesis based on earlier work that first generating alignments using simple lexical alignment techniques, followed by a separate disambiguation of alignments performs best in terms of precision and recall. The experimental results show, for example, that this combination of techniques provides an estimated precision of 0.7 for a sample of the 12,725 concepts for which alignments were generated (of the total 27,992 concepts). Thirdly, we explain our results in light of the characteristics of the vocabularies and discuss their impact on the alignments techniques.