著者

Oyama Satoshi Baba Yukino Ohmukai Ikki Dokoshi Hiroaki Kashima Hisashi

出版者

IEEE (Institute of Electrical and Electronics Engineers)

巻号頁・発行日

pp.1-9, 2015

被引用文献数

2

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Despite recent open data initiatives in many coun- tries, a significant percentage of the data provided is in non- machine-readable formats like image format rather than in a machine-readable electronic format, thereby restricting their usability. This paper describes the first unified framework for converting legacy open data in image format into a machine- readable and reusable format by using crowdsourcing. Crowd workers are asked not only to extract data from an image of a chart but also to reproduce the chart objects in spreadsheets. The properties of the reconstructed chart objects give their data structures including series names and values, which are useful for automatic processing of data by computer. Since results produced by crowdsourcing inherently contain errors, a quality control mechanism was developed that improves the accuracy of extracted tables by aggregating tables created by different workers for the same chart image and by utilizing the data structures obtained from the reproduced chart objects. Experimental results demonstrated that the proposed framework and mechanism are effective.

著者

森村 哲郎 杉山 将 鹿島 久嗣 八谷大岳 田中 利幸 Morimura Tetsuro Sugiyama Masashi Kashima Hisashi Hachiya Hirotaka Tanaka Toshiyuki

雑誌

【C】平成22年電気学会電子・情報・システム部門大会講演論文集

巻号頁・発行日

pp.178-183, 2010-09-02

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近年、分布Bellman方程式に基づくリターン(積算報酬)分布近似手法が提案され、リスク考慮型強化学習法としての有用性も示された。しかしながら、その収束性に関する解析は十分でない。そこで本報告では、動的計画法により分布Bellman方程式を解いた場合の収束性解析結果を記す。動的計画法により、リターンの初期近似分布に依存せず真のリターン分布に収束することや、真の分布のモーメントに収束する速度について報告する。

著者

Kashima Hisashi

出版者

Kyoto University

巻号頁・発行日

2007-03-23

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新制・課程博士