著者

鳥海 不二夫 榊 剛史 岡崎 直観 Fujio Toriumi Takeshi Sakaki Naoki Okazaki

雑誌

人工知能 = journal of the Japanese Society for Artificial Intelligence (ISSN:21882266)

巻号頁・発行日

vol.29, no.2, pp.172-181, 2014-03-01

著者

大矢 倫靖 中山 慎一郎 鳥海 不二夫 Tomoyasu Oya Shinichiro Nakayama Fujio Toriumi トレード・サイエンス株式会社 トレード・サイエンス株式会社 名古屋大学大学院情報科学研究科 Trade Science corporation Trade Science corporation School of Information Science Nagoya University

雑誌

人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)

巻号頁・発行日

vol.24, no.3, pp.385-391, 2009-05-01

著者

三浦 雄太郎 大阪 健吾 鳥海 不二夫 菅原 俊治 Yutaro Miura Kengo Osaka Fujio Toriumi Toshiharu Sugawara

雑誌

SIG-SAI = SIG-SAI

巻号頁・発行日

vol.28, no.4, pp.1-8, 2017-03-02

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We investigate the conditions in which cooperation is dominant in social media using the models of evolutionary games of public goods games with diminishing marginal utilities and attempt to clarify the mechanisms of prosperity of social media and effect of diminishing marginal utilities. Cooperation dominant situation corresponds to that in which social media thrives, i.e., posting articles and taking reactions by comment lead to more benefits result than do nothing as free-riders. A number of studies examined what mechanism contributes to maintain cooperation dominant situation by using evolutionary game, but their models don't include the effect of diminishing marginal utility. Thus, we developed an abstract model of social media using utility function with diminishing marginal utility and we experimentally investigated the effect of diminishing marginal utilities in the meta-rewards and SNS-norms games. The result showed that the games with diminishing marginal utility could model real SNS activities more suitably than those without it.

著者

片上 大輔 鳥海 不二夫 大澤 博隆 稲葉 通将 篠田 孝祐 松原 仁 Daisuke Katagami Fujio Toriumi Hirotaka Osawa Michimasa Inaba Kosuke Shinoda Hitoshi Matsubara 東京工芸大学工学部コンピュータ応用学科 東京大学大学院工学系研究科 筑波大学システム情報系 広島市立大学大学院情報科学研究科 電気通信大学大学院情報システム学研究科 公立はこだて未来大学システム情報科学部 Department of Applied Computer Science Faculty of Engineering Tokyo Polytechnic University Department of Applied Computer Science Faculty of Engineering The University of Tokyo Faculty of Engineering Information and Systems University of Tsukuba Graduate School of Information Sciences Hiroshima City University Graduate School of Information Systems The University of Electro-Communications Faculty of Systems Information Science Future University Hakodate

雑誌

人工知能 = journal of the Japanese Society for Artificial Intelligence (ISSN:21882266)

巻号頁・発行日

vol.30, no.1, pp.65-73, 2015-01-01

著者

岡田 佳之 榊 剛史 鳥海 不二夫 篠田 孝祐 風間 一洋 野田 五十樹 沼尾 正行 栗原 聡 Okada Yoshiyuki Takeshi Sakaki Fujio Toriumi Kosuke Shinoda Kazuhiro Kazama Itsuki Noda Masayuki Numao Satoshi Kurihara

雑誌

SIG-SAI = SIG-SAI

巻号頁・発行日

vol.16, no.1, pp.1-9, 2013-03-11

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Twitter is a famous social networking service and has received attention recently. Twitter user have increased rapidly, and many users exchange information. When 2011 Tohoku earthquake and tsunami happened, people were able to obtain information from social networking service. Though Twitter played the important role, one of the problem of Twitter, a false rumor diffusion, was pointed out. In this research, we focus on a false rumor diffusion. We propose a information diffusion model based on SIR model, classify the way of diffusion in four categories, and reapper the real diffussion by using this new model.

著者

鳥海 不二夫 Fujio Toriumi

雑誌

人工知能 = journal of the Japanese Society for Artificial Intelligence (ISSN:21882266)

巻号頁・発行日

vol.30, no.6, pp.814, 2015-11-01

著者

Yoshiyuki Okada Keisuke Ikeda Kosuke Shinoda Fujio Toriumi Takeshi Sakaki Kazuhiro Kazama Masayuki Numao Itsuki Noda Satoshi Kurihara

出版者

Fuji Technology Press Ltd.

雑誌

Journal of Advanced Computational Intelligence and Intelligent Informatics (ISSN:13430130)

巻号頁・発行日

vol.18, no.4, pp.598-607, 2014-07-20 (Released:2019-07-01)

参考文献数

11

被引用文献数

11

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Nowadays, users of Twitter, one of famous social networking service, have rapidly increased in number, and many people have been exchanging information by Twitter. When the Great East Japan Earthquake struck in 2011, people were able to obtain information from social networking services. Though Twitter played an important role, one problem was especially pointed out: false rumor diffusion. In this study, we propose an information diffusion model based on the SIR model and discuss how to prevent false rumor diffusion.

著者

JIANWEI XIE Fujio Toriumi

出版者

人工知能学会

雑誌

2018年度人工知能学会全国大会(第32回)

巻号頁・発行日

2018-04-12

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Structuring of a medical report has various applications. But most of them are only for supporting professionals to write well-structured reports, which means it cannot structurize reports without manual checks. In this study, we propose an automatic method to structurize medical image report findings. It extracts important information like disease names or symptoms in sentences and marks them with proper tags. With these tags, professionals can easily get the information they need from the report. Furthermore, we apply the method to a real dataset and get remarkably good results.