@inproceedings{hollink2008variations,
  abstract = {Evaluation of ontology alignments is in practice done in two ways: (1) assessing individual correspondences and (2) comparing the alignment to a reference alignment. However, this type of evaluation does not guarantee that an application which uses the alignment will perform well. In this paper, we contribute to the current ontology alignment evaluation practices by proposing two alternative evaluation methods that take into account some characteristics of a usage scenario without doing a full-fledged end-to-end evaluation. We compare different evaluation approaches in three case studies, focussing on methodological issues. Each case study considers an alignment between a different pair of ontologies, ranging from rich and well-structured to small and poorly structured. This enables us to conclude on the use of different evaluation approaches in different settings.},
  added-at = {2008-05-28T14:50:06.000+0200},
  address = {Berlin, Heidelberg},
  author = {Hollink, Laura and van Assem, Mark and Isaac, Antoine and Wang, Shenghui and Schreiber, Guus},
  biburl = {http://www.bibsonomy.org/bibtex/2771947296490ffa6cd01ada59cb6c1ec/eswc2008},
  booktitle = {Proceedings of the 5th European Semantic Web Conference},
  editor = {Hauswirth, Manfred and Koubarakis, Manolis and Bechhofer, Sean},
  interhash = {d903c321c17e63caff96b05d2b015ccb},
  intrahash = {771947296490ffa6cd01ada59cb6c1ec},
  keywords = {ontology end-to-end cultural retrieval evaluation semantic alignment heritage methods distance ontology-alignment},
  month = {June},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2008-05-28T14:50:06.000+0200},
  title = {Two Variations on Ontology Alignment Evaluation: Methodological Issues},
  url = {http://data.semanticweb.org/conference/eswc/2008/papers/346},
  year = 2008
}

@inproceedings{isaac2008putting,
  abstract = {Thesaurus alignment plays an important role in realising efficient access to heterogeneous Cultural Heritage data. Current ontology alignment techniques, however, provide only limited value for such access as they consider little if any requirements from realistic use cases or application scenarios. In this paper, we focus on two real-world scenarios in a library context: thesaurus merging and book re-indexing. We identify their particular requirements and describe our approach of deploying and evaluating thesaurus alignment techniques in this context. We have applied our approach for the Ontology Alignment Evaluation Initiative, and report on the performance evaluation of participants’ tools wrt. the application scenario at hand. It shows that evaluations of tools requires significant effort, but when done carefully, brings many benefits.},
  added-at = {2008-05-28T14:49:59.000+0200},
  address = {Berlin, Heidelberg},
  author = {Isaac, Antoine and Matthezing, Henk and van der Meij, Lourens and Schlobach, Stefan and Wang, Shenghui and Zinn, Claus},
  biburl = {http://www.bibsonomy.org/bibtex/2bfc09b600bc356d29ab2c236fa8216ed/eswc2008},
  booktitle = {Proceedings of the 5th European Semantic Web Conference},
  editor = {Hauswirth, Manfred and Koubarakis, Manolis and Bechhofer, Sean},
  interhash = {26d164a19aa669b289ba1ad4fc583cda},
  intrahash = {bfc09b600bc356d29ab2c236fa8216ed},
  keywords = {alignment evaluation usage ontology scenarios thesaurus ontology-alignment},
  month = {June},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2008-05-28T14:49:59.000+0200},
  title = {Putting ontology alignment in context: usage scenarios, deployment and evaluation in a library case},
  url = {http://data.semanticweb.org/conference/eswc/2008/papers/188},
  year = 2008
}

@inproceedings{spiliopoulos2008discovering,
  abstract = {For the effective alignment of ontologies, the computation of equivalence relations between elements of ontologies is not enough: Subsumption relations play a crucial role as well. In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies" (CSR) method. Given a pair of concepts from two ontologies, the objective of CSR is to identify patterns of concepts' features that provide evidence for the subsumption relation among them. This is achieved by means of a classification task, using state of the art supervised machine learning methods. For the learning of the classifiers, CSR generates training datasets from the source ontologies', considering each ontology in isolation: This allows the method to tune itself to the idiosyncrasies of each of the source ontologies. The paper describes thoroughly the method, provides experimental results over an extended version of benchmarking series and discusses the potential of the method.},
  added-at = {2008-05-28T14:49:55.000+0200},
  address = {Berlin, Heidelberg},
  author = {Spiliopoulos, Vassilis and Valarakos, Alexandros and Vouros, George},
  biburl = {http://www.bibsonomy.org/bibtex/27c1cedbbff889c129dbb35a5ae7d36c4/eswc2008},
  booktitle = {Proceedings of the 5th European Semantic Web Conference},
  editor = {Hauswirth, Manfred and Koubarakis, Manolis and Bechhofer, Sean},
  interhash = {310b8b033edc29afde6fe841f7468e15},
  intrahash = {7c1cedbbff889c129dbb35a5ae7d36c4},
  keywords = {classification supervised machine learning subsumption alignment ontology binary ontology-alignment},
  month = {June},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2008-05-28T14:49:55.000+0200},
  title = {CSR: Discovering Subsumption Relations for the Alignment of Ontologies},
  url = {http://data.semanticweb.org/conference/eswc/2008/papers/107},
  year = 2008
}