Yiou Wang


2018

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A Japanese Corpus for Analyzing Customer Loyalty Information
Yiou Wang | Takuji Tahara
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2012

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Why Question Answering using Sentiment Analysis and Word Classes
Jong-Hoon Oh | Kentaro Torisawa | Chikara Hashimoto | Takuya Kawada | Stijn De Saeger | Jun’ichi Kazama | Yiou Wang
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

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Chinese Evaluative Information Analysis
Yiou Wang | Jun’ichi Kazama | Takuya Kawada | Kentaro Torisawa
Proceedings of COLING 2012

2011

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Improving Chinese Word Segmentation and POS Tagging with Semi-supervised Methods Using Large Auto-Analyzed Data
Yiou Wang | Jun’ichi Kazama | Yoshimasa Tsuruoka | Wenliang Chen | Yujie Zhang | Kentaro Torisawa
Proceedings of 5th International Joint Conference on Natural Language Processing

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SMT Helps Bitext Dependency Parsing
Wenliang Chen | Jun’ichi Kazama | Min Zhang | Yoshimasa Tsuruoka | Yujie Zhang | Yiou Wang | Kentaro Torisawa | Haizhou Li
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

2010

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Adapting Chinese Word Segmentation for Machine Translation Based on Short Units
Yiou Wang | Kiyotaka Uchimoto | Jun’ichi Kazama | Canasai Kruengkrai | Kentaro Torisawa
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In Chinese texts, words composed of single or multiple characters are not separated by spaces, unlike most western languages. Therefore Chinese word segmentation is considered an important first step in machine translation (MT) and its performance impacts MT results. Many factors affect Chinese word segmentations, including the segmentation standards and segmentation strategies. The performance of a corpus-based word segmentation model depends heavily on the quality and the segmentation standard of the training corpora. However, we observed that existing manually annotated Chinese corpora tend to have low segmentation granularity and provide poor morphological information due to the present segmentation standards. In this paper, we introduce a short-unit standard of Chinese word segmentation, which is particularly suitable for machine translation, and propose a semi-automatic method of transforming the existing corpora into the ones that can satisfy our standards. We evaluate the usefulness of our approach on the basis of translation tasks from the technology newswire domain and the scientific paper domain, and demonstrate that it significantly improves the performance of Chinese-Japanese machine translation (over 1.0 BLEU increase).

2009

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An Error-Driven Word-Character Hybrid Model for Joint Chinese Word Segmentation and POS Tagging
Canasai Kruengkrai | Kiyotaka Uchimoto | Jun’ichi Kazama | Yiou Wang | Kentaro Torisawa | Hitoshi Isahara
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP