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- 780 creator akira-terada.
- 780 creator eiko-yamamoto.
- 780 creator hitoshi-isahara.
- 780 creator masao-utiyama.
- 780 creator yasunori-abe.
- 780 type InProceedings.
- 780 label "Application of Resource-based Machine Translation to Real Business Scenes".
- 780 sameAs 780.
- 780 abstract "As huge quantities of documents have become available, services using natural language processing technologies trained by huge corpora have emerged, such as information retrieval and information extraction. In this paper we verify the usefulness of resource-based, or corpus-based, translation in the aviation domain as a real business situation. This study is important from both a business perspective and an academic perspective. Intuitively, manuals for similar products, or manuals for different versions of the same product, are likely to resemble each other. Therefore, even with only a small training data, a corpus-based MT system can output useful translations. The corpus-based approach is powerful when the target is repetitive. Manuals for similar products, or manuals for different versions of the same product, are real-world documents that are repetitive. Our experiments on translation of manual documents are still in a beginning stage. However, the BLEU score from very small number of training sentences is already rather high. We believe corpus-based machine translation is a player full of promise in this kind of actual business scene.".
- 780 hasAuthorList authorList.
- 780 hasTopic Linguistics.
- 780 isPartOf proceedings.
- 780 keyword "Machine Translation, SpeechToSpeech Translation".
- 780 keyword "Multilinguality".
- 780 keyword "Usability, user satisfaction".
- 780 title "Application of Resource-based Machine Translation to Real Business Scenes".
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- item-1 hasContent hitoshi-isahara.
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- 783 creator eline-westerhout.
- 783 creator paola-monachesi.
- 783 type InProceedings.
- 783 label "Creating Glossaries Using Pattern-Based and Machine Learning Techniques".
- 783 sameAs 783.
- 783 abstract "One of the aims of the Language Technology for eLearning project is to show that Natural Language Processing techniques can be employed to enhance the learning process. To this end, one of the functionalities that has been developed is a pattern-based glossary candidate detector which is capable of extracting definitions in eight languages. In order to improve the results obtained with the pattern-based approach, machine learning techniques are applied on the Dutch results to filter out incorrectly extracted definitions. In this paper, we discuss the machine learning techniques used and we present the results of the quantitative evaluation. We also discuss the integration of the tool into the Learning Management System ILIAS.".
- 783 hasAuthorList authorList.
- 783 hasTopic Linguistics.
- 783 isPartOf proceedings.
- 783 keyword "Information Extraction, Information Retrieval".
- 783 keyword "Lexicon, lexical database".
- 783 keyword "Tools, systems, applications".
- 783 title "Creating Glossaries Using Pattern-Based and Machine Learning Techniques".
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- 784 creator dirk-geeraerts.
- 784 creator kris-heylen.
- 784 creator simon-de-deyne.
- 784 creator yves-peirsman.
- 784 type InProceedings.
- 784 label "The Construction and Evaluation of Word Space Models".
- 784 sameAs 784.
- 784 abstract "Semantic similarity is a key issue in many computational tasks. This paper goes into the development and evaluation of two common ways of automatically calculating the semantic similarity between two words. On the one hand, such methods may depend on a manually constructed thesaurus like (Euro)WordNet. Their performance is often evaluated on the basis of a very restricted set of human similarity ratings. On the other hand, corpus-based methods rely on the distribution of two words in a corpus to determine their similarity. Their performance is generally quantified through a comparison with the judgements of the first type of approach. This paper introduces a new Gold Standard of more than 5,000 human intra-category similarity judgements. We show that corpus-based methods often outperform (Euro)WordNet on this data set, and that the use of the latter as a Gold Standard for the former, is thus often far from ideal.".
- 784 hasAuthorList authorList.
- 784 hasTopic Linguistics.
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- 784 keyword "Evaluation methodologies".
- 784 keyword "Information Extraction, Information Retrieval".
- 784 keyword "Semantics".
- 784 title "The Construction and Evaluation of Word Space Models".
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