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Transactions of The Japanese Society for Artificial Intelligence最新文献

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Slot Filling with Data Augmentation That Allows the Use of Keyword and Context Information for Handling Unknown Slot Values 槽位填充与数据增强，允许使用关键字和上下文信息来处理未知的槽位值
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_ids-d
Yuka Kobayashi, Tsuyoshi Kushima, Takami Yoshida, Hiroshi Fujimura, Kenji Iwata
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引用次数: 0
Estimating Time-Series Changes in Social Sensitivity for COVID-19 @ Twitter in Japan 估计日本对COVID-19 @ Twitter的社会敏感性的时间序列变化
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_c-l91
R. Saito, S. Haruyama
The global outbreak of COVID-19 is now putting enormous pressure on society to change our traditional social behavior. Government officials are also forced to make short-term decisions based on limited information for public health, and investor sentiment about the infection situation in each country has a significant impact on the stock market. In this paper, we attempt to visualize the time series of indexed social sentiment in Japan under the COVID-19 pandemic by using a neural network approach, and clarify changes in the sensitivity of citizens to the coronavirus. The sentiment was classified for Twitter tweets that matched the keywords for which the government was asked to restrict action, and sentiment trends were identified for the period from before the outbreak to the fifth wave of infection in Tokyo, Sapporo, Osaka, and Fukuoka. The indices obtained show a correlation with the number of infected cases by region and with national and local events, and in global cities such as Tokyo and Osaka as they experienced waves of infections and emergency declarations, sensitivity gradually became paralyzed, and parallel trends in sentiment waveforms were observed among regions. © 2022, Japanese Society for Artificial Intelligence.
新冠肺炎的全球爆发给社会带来了巨大压力，要求改变我们的传统社会行为。政府官员还被迫根据有限的公共卫生信息做出短期决定，投资者对每个国家感染情况的情绪对股市都有重大影响。在本文中，我们试图通过使用神经网络方法可视化新冠肺炎大流行下日本社会情绪指数的时间序列，并阐明公民对冠状病毒敏感性的变化。对推特推文中与政府被要求限制行动的关键词相匹配的情绪进行了分类，并确定了从疫情爆发前到东京、札幌、大阪和福冈第五波感染期间的情绪趋势。所获得的指数显示，各地区的感染病例数以及国家和地方事件之间存在相关性，在东京和大阪等全球城市，随着感染浪潮和紧急状态宣言的爆发，敏感性逐渐减弱，各地区之间的情绪波形呈平行趋势。©2022，日本人工智能学会。
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引用次数: 0
A Proposal and Implement in Non-task-oriented Dialogue System of Risky Politeness Strategy 风险礼貌策略在非任务导向对话系统中的提出与实施
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_ids-g
T. Miyamoto, Nozomu Nagai, Yuto Mitsuta, Motoki Iwashita, Mizuki Endo, Akihiro Suzuki, D. Katagami
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引用次数: 0
Evaluation of a Daily Interactive Chatbot That Exchanges Information about Others through Long-Term Use in a Group of Friends 通过在朋友群中长期使用来交换他人信息的每日互动聊天机器人的评估
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_ids-i
Seiya Mitsuno, Y. Yoshikawa, Midori Ban, H. Ishiguro
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引用次数: 0
Analysis of Information Search around the Time of Childbirth: Estimating Probability Distributions of Search Dates via Mathematical Optimization 分娩前后的信息搜索分析:通过数学优化估计搜索日期的概率分布
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_d-l74
J. Iwanaga, Naoki Nishimura, Noriyoshi Sukegawa, Yuichi Takano
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引用次数: 0
Ethical Risks of Intelligent Dialogue Systems from View of European Trends on AI 从欧洲人工智能趋势看智能对话系统的伦理风险
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_ids-a
T. Ichikawa
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引用次数: 0
Improvement of Task Allocation in TP Algorithm for MAPD Problem by Relaxation of Movement Limitation and Estimation of Pickup Time 放宽运动限制和估计取货时间对MAPD问题TP算法任务分配的改进
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-05-01 DOI: 10.1527/tjsai.37-3_a-l84
Masanori Shimokawa, T. Matsui
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引用次数: 0
Diverse Dialogue Generation by Deep Learning Methods Using Loss Function IncorporatingWord Statistics 利用损失函数结合单词统计的深度学习方法生成多样化的对话
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-03-01 DOI: 10.1527/tjsai.37-2_g-l62
Ayaka Ueyama, Yoshinobu Kano
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引用次数: 0
A Distributed Asynchronous Heuristic Algorithm in Generalized Mutual Assignment Problem 广义相互指派问题中的一种分布式异步启发式算法
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-03-01 DOI: 10.1527/tjsai.37-2_b-l81
Kenta Hanada, Yuki Amemiya, Kenji Sugimoto
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引用次数: 1
Constructing a Model for Estimating Learners’ Mental States Using Biometric Information and Reducing Labeling Costs Using Deep Learning 利用生物识别信息构建学习者心理状态评估模型并利用深度学习降低标签成本
Transactions of The Japanese Society for Artificial Intelligence
Pub Date : 2022-03-01 DOI: 10.1527/tjsai.37-2_c-66
Yoshihisa Furusawa, Yoshimasa Tawatsuji, T. Matsui
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引用次数: 0
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