Jun′ichi Kazama

Also published as: Jun’ichi Kazama


2013

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Minimally Supervised Method for Multilingual Paraphrase Extraction from Definition Sentences on the Web
Yulan Yan | Chikara Hashimoto | Kentaro Torisawa | Takao Kawai | Jun’ichi Kazama | Stijn De Saeger
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2012

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Chinese Evaluative Information Analysis
Yiou Wang | Jun’ichi Kazama | Takuya Kawada | Kentaro Torisawa
Proceedings of COLING 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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Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web
Chikara Hashimoto | Kentaro Torisawa | Stijn De Saeger | Jong-Hoon Oh | Jun’ichi Kazama
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

2011

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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

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Relation Acquisition using Word Classes and Partial Patterns
Stijn De Saeger | Kentaro Torisawa | Masaaki Tsuchida | Jun’ichi Kazama | Chikara Hashimoto | Ichiro Yamada | Jong Hoon Oh | Istvan Varga | Yulan Yan
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

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Learning with Lookahead: Can History-Based Models Rival Globally Optimized Models?
Yoshimasa Tsuruoka | Yusuke Miyao | Jun’ichi Kazama
Proceedings of the Fifteenth Conference on Computational Natural Language Learning

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Extracting Paraphrases from Definition Sentences on the Web
Chikara Hashimoto | Kentaro Torisawa | Stijn De Saeger | Jun’ichi Kazama | Sadao Kurohashi
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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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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Similarity Based Language Model Construction for Voice Activated Open-Domain Question Answering
István Varga | Kiyonori Ohtake | Kentaro Torisawa | Stijn De Saeger | Teruhisa Misu | Shigeki Matsuda | Jun’ichi Kazama
Proceedings of 5th International Joint Conference on Natural Language Processing

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Extending WordNet with Hypernyms and Siblings Acquired from Wikipedia
Ichiro Yamada | Jong-Hoon Oh | Chikara Hashimoto | Kentaro Torisawa | Jun’ichi Kazama | Stijn De Saeger | Takuya Kawada
Proceedings of 5th International Joint Conference on Natural Language Processing

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Toward Finding Semantic Relations not Written in a Single Sentence: An Inference Method using Auto-Discovered Rules
Masaaki Tsuchida | Kentaro Torisawa | Stijn De Saeger | Jong-Hoon Oh | Jun’ichi Kazama | Chikara Hashimoto | Hayato Ohwada
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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A Look inside the Distributionally Similar Terms
Kow Kuroda | Jun’ichi Kazama | Kentaro Torisawa
Proceedings of the Second Workshop on NLP Challenges in the Information Explosion Era (NLPIX 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).

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Improving Graph-based Dependency Parsing with Decision History
Wenliang Chen | Jun’ichi Kazama | Yoshimasa Tsuruoka | Kentaro Torisawa
Coling 2010: Posters

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Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants
Masahiro Kojima | Masaki Murata | Jun’ichi Kazama | Kow Kuroda | Atsushi Fujita | Eiji Aramaki | Masaaki Tsuchida | Yasuhiko Watanabe | Kentaro Torisawa
Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation

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Bitext Dependency Parsing with Bilingual Subtree Constraints
Wenliang Chen | Jun’ichi Kazama | Kentaro Torisawa
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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A Bayesian Method for Robust Estimation of Distributional Similarities
Jun’ichi Kazama | Stijn De Saeger | Kow Kuroda | Masaki Murata | Kentaro Torisawa
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

2009

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Multilingual Dependency Learning: Exploiting Rich Features for Tagging Syntactic and Semantic Dependencies
Hai Zhao | Wenliang Chen | Jun’ichi Kazama | Kiyotaka Uchimoto | Kentaro Torisawa
Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL 2009): Shared Task

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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

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Improving Dependency Parsing with Subtrees from Auto-Parsed Data
Wenliang Chen | Jun’ichi Kazama | Kiyotaka Uchimoto | Kentaro Torisawa
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Hypernym Discovery Based on Distributional Similarity and Hierarchical Structures
Ichiro Yamada | Kentaro Torisawa | Jun’ichi Kazama | Kow Kuroda | Masaki Murata | Stijn De Saeger | Francis Bond | Asuka Sumida
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Large-Scale Verb Entailment Acquisition from the Web
Chikara Hashimoto | Kentaro Torisawa | Kow Kuroda | Stijn De Saeger | Masaki Murata | Jun’ichi Kazama
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

2008

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Inducing Gazetteers for Named Entity Recognition by Large-Scale Clustering of Dependency Relations
Jun’ichi Kazama | Kentaro Torisawa
Proceedings of ACL-08: HLT

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Looking for Trouble
Stijn De Saeger | Kentaro Torisawa | Jun’ichi Kazama
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

2007

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A New Perceptron Algorithm for Sequence Labeling with Non-Local Features
Jun’ichi Kazama | Kentaro Torisawa
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

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Exploiting Wikipedia as External Knowledge for Named Entity Recognition
Jun’ichi Kazama | Kentaro Torisawa
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

2006

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Semantic Role Recognition Using Kernels on Weighted Marked Ordered Labeled Trees
Jun’ichi Kazama | Kentaro Torisawa
Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X)

2005

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Automatic Discovery of Attribute Words from Web Documents
Kosuke Tokunaga | Jun’ichi Kazama | Kentaro Torisawa
Second International Joint Conference on Natural Language Processing: Full Papers

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Speeding up Training with Tree Kernels for Node Relation Labeling
Jun’ichi Kazama | Kentaro Torisawa
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

2003

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Evaluation and Extension of Maximum Entropy Models with Inequality Constraints
Jun’ichi Kazama | Jun’ichi Tsujii
Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing

2002

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Tuning support vector machines for biomedical named entity recognition
Jun’ichi Kazama | Takaki Makino | Yoshihiro Ohta | Jun’ichi Tsujii
Proceedings of the ACL-02 Workshop on Natural Language Processing in the Biomedical Domain