@inproceedings{17076,
author       = {Tordai, A. and van Ossenbruggen, J. R. and Schreiber, G. and Wielinga, B.},
title        = {Aligning {Large} {S{KOS}-}{Like} {Vocabularies}},
booktitle    = {Proceedings of European Semantic Web Conference 2010 (7)},
conferencetitle    = {European Semantic Web Conference},
conferencedate     = {2010, May 30 - June 3},
conferencelocation = {Heraklion, Crete, Greece},
series       = {Lecture Notes in Computer Science},
pages        = {198 - 212},
year         = {2010},
month        = {May},
volume       = {6088},
publisher    = {Springer},
isbn         = {978-3-642-13485-2},
issn         = {0302-9743},
refereed     = {y},
size         = {15p.},
group        = {INS2},
language     = {en},
project      = {Non-NWO Project 1},
abstract     = {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.},
url          = {http://dx.doi.org/10.1007/978-3-642-13486-9_14},
}

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