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- item-1 hasContent stephane-huet.
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- item-2 hasContent guillaume-gravier.
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- 175 creator dashtseren-erdenebat.
- 175 creator hiroyuki-kaji.
- 175 creator shin-ichi-tamamura.
- 175 type InProceedings.
- 175 label "Automatic Construction of a Japanese-Chinese Dictionary via English".
- 175 sameAs 175.
- 175 abstract "This paper proposes a method of constructing a dictionary for a pair of languages from bilingual dictionaries between each of the languages and a third language. Such a method would be useful for language pairs for which wide-coverage bilingual dictionaries are not available, but it suffers from spurious translations caused by the ambiguity of intermediary third-language words. To eliminate spurious translations, the proposed method uses the monolingual corpora of the first and second languages, whose availability is not as limited as that of parallel corpora. Extracting word associations from the corpora of both languages, the method correlates the associated words of an entry word with its translation candidates. It then selects translation candidates that have the highest correlations with a certain percentage or more of the associated words. The method has the following features. It first produces a domain-adapted bilingual dictionary. Second, the resulting bilingual dictionary, which not only provides translations but also associated words supporting each translation, enables contextually based selection of translations. Preliminary experiments using the EDR Japanese-English and LDC Chinese-English dictionaries together with Mainichi Newspaper and Xinhua News Agency corpora demonstrate that the proposed method is viable. The recall and precision could be improved by optimizing the parameters.".
- 175 hasAuthorList authorList.
- 175 hasTopic Linguistics.
- 175 isPartOf proceedings.
- 175 keyword "Lexicon, lexical database".
- 175 keyword "Machine Translation, SpeechToSpeech Translation".
- 175 keyword "Multilinguality".
- 175 title "Automatic Construction of a Japanese-Chinese Dictionary via English".
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- item-1 hasContent hiroyuki-kaji.
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- item-2 hasContent shin-ichi-tamamura.
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- item-3 hasContent dashtseren-erdenebat.
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- 176 creator tomas-by.
- 176 type InProceedings.
- 176 label "The Kalshnikov 691 Dependency Bank".
- 176 sameAs 176.
- 176 abstract "The PARC 700 dependency bank has a number of features that would seem to make it less than optimally suited for its intended purpose, parser evaluation. However, it is difficult to know precisely what impact these problems have on the evaluation results, and as a first step towards making comparison possible, a subset of the same sentences is presented here, marked up using a different format that avoids them. In this new representation, the tokens contain exactly the same sequence of characters as the original text, word order is encoded explicitly, and there is no artificial distinction between full tokens and attribute tokens. There is also a clear division between word tokens and empty nodes, and the token attributes are stored together with the word, instead of being spread out individually in the file. A standard programming language syntax is used for the data, so there is little room for markup errors. Finally, the dependency links are closer to standard grammatical terms, which presumably makes it easier to understand what they mean and to convert any particular parser output format to the Kalashnikov 691 representation. The data is provided both in machine-readable format and as graphical dependency trees.".
- 176 hasAuthorList authorList.
- 176 hasTopic Linguistics.
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- 176 keyword "Corpus (creation, annotation, etc.)".
- 176 keyword "Standards for LRs".
- 176 keyword "Validation of LRs".
- 176 title "The Kalshnikov 691 Dependency Bank".
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- 177 creator dietrich-klakow.
- 177 creator jochen-l-leidner.
- 177 creator michael-wiegand.
- 177 type InProceedings.
- 177 label "Cost-Sensitive Learning in Answer Extraction".
- 177 sameAs 177.
- 177 abstract "One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. In an ordinary training set, there are far more incorrect answers than correct answers. The class-imbalance is, thus, inherent to the classification task. It has a deteriorating effect on the performance of classifiers trained by standard machine learning algorithms. They usually have a heavy bias towards the majority class, i.e. the class which occurs most often in the training set. In this paper, we propose a method to tackle class imbalance by applying some form of cost-sensitive learning which is preferable to sampling. We present a simple but effective way of estimating the misclassification costs on the basis of class distribution. This approach offers three benefits. Firstly, it maintains the distribution of the classes of the labeled training data. Secondly, this form of meta-learning can be applied to a wide range of common learning algorithms. Thirdly, this approach can be easily implemented with the help of state-of-the-art machine learning software.".
- 177 hasAuthorList authorList.
- 177 hasTopic Linguistics.
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- 177 keyword "Acquisition, Machine Learning".
- 177 keyword "Question Answering".
- 177 keyword "Statistical methods".
- 177 title "Cost-Sensitive Learning in Answer Extraction".
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- item-1 hasContent michael-wiegand.
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- 184 creator hennie-van-der-vliet.
- 184 creator isa-maks.
- 184 creator piek-vossen.
- 184 creator roxane-segers.
- 184 type InProceedings.
- 184 label "Adjectives in the Dutch Semantic Lexical Database CORNETTO".