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courses:rg:cross-lingual_ontology_alignment [2010/12/05 20:11]
abzianidze vytvořeno 		courses:rg:cross-lingual_ontology_alignment [2011/06/25 20:27] (current)
abzianidze
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 {{https://wiki.ufal.ms.mff.cuni.cz/_media/courses:rg:bouma_lrec10.pdf | Cross-lingual Ontology Alignment using EuroWordNet and Wikipedia }} {{https://wiki.ufal.ms.mff.cuni.cz/_media/courses:rg:bouma_lrec10.pdf | Cross-lingual Ontology Alignment using EuroWordNet and Wikipedia }}
 The International Conference on Language Resources and Evaluation (LREC) 2010 The International Conference on Language Resources and Evaluation (LREC) 2010
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 +report by **Lasha Abzianidze**
  
 ===== Introduction ===== ===== Introduction =====
 The paper is about cross-lingual ontology alignment - to map thesauri in different languages and to map resources that are large, rich in semantics but weak in formal structure. The paper is about cross-lingual ontology alignment - to map thesauri in different languages and to map resources that are large, rich in semantics but weak in formal structure.
-The author describes a system for linking the thesaurus of the Netherlands Institute for Sound and Vision (GTAA) to English WordNet and dbpedia. He describes both approaches his group used for the alignment tasks: GTTA - English WordNet and GTTA-English dbpedia. For each alignment the evaluation is presented and compared with another system's results, which was also taking on the challenge of the Very Large Cross-Lingual Recourses (VLCR) task of the Ontology Alignment Evaluation Initiative (OAEI) workshop 2009.+The author describes a system for linking the thesaurus of the Netherlands Institute for Sound and Vision ([[http://instituut.beeldengeluid.nl/index.aspx?ChapterID=8532|GTAA]]) to English [[http://wordnet.princeton.edu| WordNet]] and [[http://dbpedia.org/About| DBpedia]]. He describes both approaches his group used for the alignment tasks: GTTA - English WordNet (illustrated on the left image) and GTTA-English dbpedia (illustrated on the right image). For each alignment the evaluation is presented and compared with another system's results, which was also taking on the challenge of the Very Large Cross-Lingual Recourses ([[http://oaei.ontologymatching.org/2009/vlcr/|VLCR]]) task of the Ontology Alignment Evaluation Initiative ([[http://oaei.ontologymatching.org/2009/vlcr/|OAEI]]) workshop 2009. 
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 +{{:courses:rg:gtaa_wordnet.png}}   {{:courses:rg:gtaa_wikipedia.png}}
  
 ===== Comments ===== ===== Comments =====
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   * In the paper, there is no details how they are calculating evaluation. We suppose that they are using following widely used method: To evaluate the resulting alignment A we compare it to a reference/sample alignment (R) based on some criterion. The usual approach for evaluating the returned alignments is to consider them as sets of correspondences (pairs) and to apply precision and recall originating from information retrieval:     <latex>P = |R ∩ A| / |A|</latex>      <latex>R = |R ∩ A| /|R|</latex>    where <latex> P </latex> - Precision, <latex> R </latex>- recall; <latex>|R ∩ A|</latex> - The number of true positives; <latex>|A|</latex> - The number of the retrieved correspondences; <latex>|R|</latex> - The number of expected correspondences.   * In the paper, there is no details how they are calculating evaluation. We suppose that they are using following widely used method: To evaluate the resulting alignment A we compare it to a reference/sample alignment (R) based on some criterion. The usual approach for evaluating the returned alignments is to consider them as sets of correspondences (pairs) and to apply precision and recall originating from information retrieval:     <latex>P = |R ∩ A| / |A|</latex>      <latex>R = |R ∩ A| /|R|</latex>    where <latex> P </latex> - Precision, <latex> R </latex>- recall; <latex>|R ∩ A|</latex> - The number of true positives; <latex>|A|</latex> - The number of the retrieved correspondences; <latex>|R|</latex> - The number of expected correspondences.
   * The task [[http://oaei.ontologymatching.org/2009/vlcr/|Very Large Cross-lingual Resources]](VLCR) on the [[http://oaei.ontologymatching.org/2009/|Ontology Alignment Evaluation Initiative]] (OAEI) workshop and about its [[http://oaei.ontologymatching.org/2009/vlcr/|evaluation]].   * The task [[http://oaei.ontologymatching.org/2009/vlcr/|Very Large Cross-lingual Resources]](VLCR) on the [[http://oaei.ontologymatching.org/2009/|Ontology Alignment Evaluation Initiative]] (OAEI) workshop and about its [[http://oaei.ontologymatching.org/2009/vlcr/|evaluation]].
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 +\\
 +> Interesting thing - 67% of the terms from the GTAA (Duch linguistic resource) can be mapped to the Duch WordNet. It is much more, than the coverage of Czech WordNet over the terms from PDT (Prague Dependency Treebank). -MK-
 +> It has shown, that the cross-language links are not reversible, they are in relation n:n (many to many).-MK-
  
 ===== What do we like about the paper ===== ===== What do we like about the paper =====
   * Approaches are described and visualized clearly.   * Approaches are described and visualized clearly.
   * Overcome/existing problems are described clearly with their examples.   * Overcome/existing problems are described clearly with their examples.
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 ===== What do we dislike about the paper ===== ===== What do we dislike about the paper =====
   * There is not enough information about the sample of results used during the evaluation.   * There is not enough information about the sample of results used during the evaluation.
   * We cannot find precisely according to which formulas were precision and recall computed.    * We cannot find precisely according to which formulas were precision and recall computed. 
   * Some missing numbers in the tables are confusing.    * Some missing numbers in the tables are confusing. 
-\\ +\\ written by //[[lasha.abzianidze@gmail.com|Lasha Abzianidze]]//
-written by Lasha Abzianidze+

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