Annotating Event Appearance for Japanese Chess Commentary Corpus.
Hirotaka Kameko; Shinsuke Mori
Proceedings of the twelfth edition of the Language Resources and Evaluation Conference, 2020, Peer-reviewed, Lead author
Deep Reinfocement Learning for Sparse Reward Environments
水上 直紀; 鈴木 潤; 亀甲 博貴; 鶴岡 慶雅
情報処理学会論文誌, Mar. 2019, Peer-reviewed
Deep Reinforcement Learning with Hidden Layers on Future States
Hirotaka Kameko; Jun Suzuki; Naoki Mizukami; Yoshimasa Tsuruoka
Communications in Computer and Information Science, 2018, Peer-reviewed, Lead author
Annotating Modality Expressions and Event Factuality for a Japanese Chess Commentary Corpus.
Suguru Matsuyoshi; Hirotaka Kameko; Yugo Murawaki; Shinsuke Mori
Proceedings of the Eleventh International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan, May 7-12, 2018., 2018, Peer-reviewed
Predicting Moves in Comments for Shogi Commentary Generation
SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 07 Aug. 2017, Peer-reviewed
Improvement in Domain Specific Word Segmentation by Symbol Grounding
Tomori Suzushi; Kameko Hirotaka; Ninomiya Takashi; Mori Shinsuke; Tsuruoka Yoshimasa
Journal of Natural Language Processing, 2017, Peer-reviewed
Exploration bonuses based on upper confidence bounds for sparse reward games
Naoki Mizukami; Jun Suzuki; Hirotaka Kameko; Yoshimasa Tsuruoka
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, Peer-reviewed
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, Portorož, Slovenia, May 23-28, 2016., 2016, Peer-reviewed
Can Symbol Grounding Improve Low-Level NLP? Word Segmentation as a Case Study.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, September 17-21, 2015, 2015, Peer-reviewed, Lead author
Learning a Game Commentary Generator with Grounded Move Expressions