@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{kiefer2008creation,
  abstract = {This research explores our novel method for Semantic Web service matchmaking based on iSPARQL queries, which enable the user to query the Semantic Web with techniques from traditional information retrieval. The strategies for matchmaking which we develop and evaluate in the paper make use of a plethora of similarity measures and combination functions from SimPack -- our library of similarity measures for the use in ontologies. We show how our combination of structured and imprecise querying can be used to perform hybrid Semantic Web service matchmaking in simple and amazingly fast fashion. We analyze our approach thoroughly on a large OWL-S service test collection, and show how our initial strategies can be improved by applying machine learning algorithms such as regression, decision trees, or support vector machines to result in the most effective strategies for matchmaking.},
  added-at = {2008-05-28T14:49:57.000+0200},
  address = {Berlin, Heidelberg},
  author = {Kiefer, Christoph and Bernstein, Abraham},
  biburl = {http://www.bibsonomy.org/bibtex/24058a55f996d8c24ef69c32f3c81ccdd/eswc2008},
  booktitle = {Proceedings of the 5th European Semantic Web Conference},
  editor = {Hauswirth, Manfred and Koubarakis, Manolis and Bechhofer, Sean},
  interhash = {88ebc745190a2df9e0990f15ea2cdda7},
  intrahash = {4058a55f996d8c24ef69c32f3c81ccdd},
  keywords = {retrieval information matchmaking machine learning sparql evaluation query-processing-1},
  month = {June},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2008-05-28T14:49:57.000+0200},
  title = {The Creation and Evaluation of iSPARQL Strategies for Matchmaking},
  url = {http://data.semanticweb.org/conference/eswc/2008/papers/133},
  year = 2008
}

@inproceedings{kiefer2008adding,
  abstract = {In machine learning/data mining, people have been exploring how to learn models of relational data for a long time. The rational behind this is that exploiting the rich and complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. These links are usually hard to model by traditional propositional learning techniques.  We extend this idea to the Semantic Web. In this paper we introduce a novel approach we call SPARQL-ML to perform data mining for Semantic Web data. Our approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers.  We analyze our approach thoroughly conducting three sets of experiments on synthetic as well as real-world datasets. Our analytical results show that our approach can be used for any Semantic Web dataset to perform instance-based learning and classification. A comparison to kernel methods used in Support Vector Machines shows that our approach is superior in terms of classification accuracy. Moreover, we show how our approach can be used for Semantic Web service classification and automatic semantic annotation.},
  added-at = {2008-05-28T14:49:52.000+0200},
  address = {Berlin, Heidelberg},
  author = {Kiefer, Christoph and Bernstein, Abraham and Locher, André},
  biburl = {http://www.bibsonomy.org/bibtex/2569e52ad749e5ea312aae2a76dca52d7/eswc2008},
  booktitle = {Proceedings of the 5th European Semantic Web Conference},
  editor = {Hauswirth, Manfred and Koubarakis, Manolis and Bechhofer, Sean},
  interhash = {c091f27b3e3d70203862e2f3a1132928},
  intrahash = {569e52ad749e5ea312aae2a76dca52d7},
  keywords = {sparql data statistical evaluation mining relational learning query-processing-1},
  month = {June},
  publisher = {Springer Verlag},
  series = {LNCS},
  timestamp = {2008-05-28T14:49:52.000+0200},
  title = {Adding Data Mining Support to SPARQL via Statistical Relational Learning Methods},
  url = {http://data.semanticweb.org/conference/eswc/2008/papers/32},
  year = 2008
}