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1 0 0 0 OA 册府元龜1000卷目10卷

著者: 宋王欽若等奉敕撰
出版者: 黄國〓校刊
巻号頁・発行日: vol.[104], 1642

2018-02-14 00:00:10
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1 0 0 0 OA 二如亭群芳譜

著者: 明王象晉撰
巻号頁・発行日: vol.[19], 1000

2018-02-11 14:00:07
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1 0 0 0 OA 玉海卷1-151,156-204附刻13種

著者: 宋王應麟撰
出版者: 慶元路儒學刊萬暦遞修刊
巻号頁・発行日: vol.[35], 1000

2018-02-09 17:00:08
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1 0 0 0 OA 博古圖録考正30卷

著者: 宋王黼等撰
出版者: 鄭樸校刊
巻号頁・発行日: vol.[1], 1596

2018-02-07 03:00:06
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1 0 0 0 OA 孔子家語

著者: (魏) 王肅註
出版者: [出版者不明]
巻号頁・発行日: vol.卷3-4, 1600

2018-02-06 07:00:06
1 + 0 Twitter

1 0 0 0 OA 複合施設におけるツイートの時空間分析に基づくタグクラウドを用いた可視化システム

著者: 王元元丸山直樹河合由起子秋山豊和角谷和俊
出版者: 一般社団法人人工知能学会
雑誌: 人工知能学会論文誌 (ISSN:13460714)
巻号頁・発行日: vol.32, no.1, pp.WII-I_1-11, 2017-01-06 (Released:2017-01-25)
参考文献数: 19
被引用文献数: 1

Twitter evidently stirred a popular trend of personal update sharing. Twitter users can be kept up to date with current information from Twitter; however, users cannot obtain the most recent information, while they browse web pages since these are not updated in real time. Meanwhile, there are many events happen at any time such as crowded restaurants and time sales in different floors or areas at composite facilities in urban areas. To solve them, it is thought that an appropriate method is to detect tweets of small-scale facilities at a composite facility to enrich their traditional web pages. Therefore, we developed a tweet visualization system to support users grasp event happens over time and space from tweets while they browse any web pages based on spatio-temporal analysis of tweets. In order to detect and analyze tweets of a composite facility, the system maps geo-tagged tweets to web pages by matching their location names, and classifies the tweets into different categories of small-scale facilities by utilizing machine learning algorithms. Thus, the system can visualize tweets in a tag cloud is associated with a web page to help users immediately gain a quick overview of events through space and time while they browse this web page, and it can also effectively present a list of most related tweets to help users obtain more detailed information about events. In this paper, we discuss our spatio-temporal analysis method and we have also included an evaluation of tweet classification into small-scale facilities and tag cloud generation that feature words of tweets are changed over time.