Summary of the paper

Title Linking Korean Words with an Ontology
Authors Min-Jae Kwon, Hae-Yun Lee and Hee-Rahk Chae
Abstract The need for ontologies has increased in computer science or information science recently. Especially, NLP systems such as information retrieval, machine translation, etc. require ontologies whose concepts are connected to natural language words. There are a few Korean wordnets such as U-WIN, KorLex, CoreNet, etc. Most of them, however, stand alone without any link to an ontology. Hence, we need a Korean wordnet which is linked to a language-neutral ontology such as SUMO, OpenCyc, DOLCE, etc. In this paper, we will present a method of linking Korean word senses with the concepts of an ontology, which is part of an ongoing project. We use a Korean-English bilingual dictionary, Princeton WordNet (Fellbaum 1998), and the ontology SmartSUMO (Oberle et al. 2007). The current version of WordNet is mapped into SUMO, which constitutes a major part of SmartSUMO. We focus on mapping Korean word senses with corresponding English word senses by way of Princeton WordNet which is mapped into SUMO. This paper will show that we need to apply different algorithms of linking, depending on the information types that a bilingual dictionary contains.
Topics Ontologies, Lexicon, lexical database, LR national/international projects, organizational/policy issues
Full paper Linking Korean Words with an Ontology
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Bibtex @InProceedings{KWON10.586,
  author = {Min-Jae Kwon and Hae-Yun Lee and Hee-Rahk Chae},
  title = {Linking Korean Words with an Ontology},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
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