著者

浅野 優 小出 誠二 岩山 真 加藤 文彦 小林 厳生 美馬 正司 大向 一輝 武田 英明

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

pp.LOD-27, (Released:2017-01-31)

参考文献数

19

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We describe a procedure for constructing a website for publishing open data by focusing on the case of Open DATA METI, a website of the Ministry of Economy, Trade, and Industry. We developed two sites for publishing open data: a data catalog site and one for searching linked open data (LOD). The former allows users to find relevant data they want to use, and the latter allows them to utilize the found data by connecting them. To implement the data catalog site, we constructed a site tailored to the needs of the organization. Then we extracted a large amount of metadata from the individual open data and put it on the site. These activities would have taken a lot of time if we had used the existing methods, so we devised our own solutions for them. To implement the LOD searching site, we converted the data into LOD form in the Resource Description Framework (RDF). We focused on converting statistical data into tables, which are widely used. Regarding the conversion, there were several kinds of missing information that we needed to associate with the data in the tables. We created a template for incorporating the necessary information for LOD in the original table. The conversion into LOD was automatically done using the template.

著者

泉田 直己 浅野 優 保崎 純郎 川野 誠子 沢登 徹 平岡 昌和

出版者

一般社団法人 日本不整脈心電学会

雑誌

心電図 (ISSN:02851660)

巻号頁・発行日

vol.17, no.6, pp.679-686, 1997-11-25 (Released:2010-09-09)

参考文献数

15

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QT時間延長児の重症不整脈の危険度を明らかにするために, その再分極の不均一性の指標としてactivation reoovery interval (ARI) のdispersionを失神の既往のあるJervell and Lange-Nielsen症候群例と失神のない低力ルシウム血症によるQT延長児で調べ, 同年代の正常例と比較した.ARlは, 体表面87点から記録した心電図波形の一次微分のQRS区間での最小点とSTT区間でのdV/dtの最大点間の時間とし, 全体での最長値と最短値の差をARIのdispersionとした.ARI値の分布パターンは正常例とQT延長例のいずれもほぼ同様のパターンを示したがARI disperlionは失神発作のあるQT延長例で明らかに高値を示した.この結果は, 心室性不整脈による失神発作があるQT延長例での再分極の不均一性の増大と一致するものと考えられた.ARI dispersionは小児QT延長例における失神の危険度の判定因子として利用できる可能性が示された.

著者

浅野 優 横手 健一

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第36回 (2022)

巻号頁・発行日

pp.4D3GS603, 2022 (Released:2022-07-11)

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文書内における個人情報の匿名化や情報抽出などを目的に固有表現を抽出しようとする際、機械学習をはじめとする統計的アプローチでは、類似表記に対して異なるラベルが付与されることがある。同一のラベルを一貫して付与する方が望ましい場合、それを判定できれば、ラベル付与の精度を改善できる。 本研究はこのような固有表現の一貫性を判定する手法を提案する。拡張固有表現タグ付きコーパスを用いた実験では、ベースラインから精度の向上を確認した。

著者

浅野 優 田中 譲

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.26, no.1, pp.248-261, 2011 (Released:2011-01-06)

参考文献数

16

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This paper describes a new framework for querying the Semantic Web using a rich vocabulary. This framework consists of two mechanisms; one for building a rich vocabulary based on lexicographic semantics, and the other for evaluating queries using such a vocabulary. A vocabulary built by the former mechanism has the following two features: (a) its richness because of its expandability and (b) the lexicographic-semantic definition of its words. Query expressions using such a rich vocabulary satisfy the following two properties: (c) no need to use nested query structures, and (d) no need to use variables. In our framework, a new word, i.e., a derived word, can be defined as a character string label given to an expression that combines already defined words with operators. This expression, or phrase, works as a lexicographic definition of this derived word. Each vocabulary consists of basic words and derived words. A lexicon of a vocabulary denotes a set of lexicographic definitions of all of its derived words. Once someone defines a lexicon of a large vocabulary with all of its basic words being mapped to an ontology of the Semantic Web, users can query this Semantic Web using this vocabulary. The same lexicon can be reused for the Semantic Web that has a different ontology if all of its basic words are newly mapped to its ontology. Use of a rich vocabulary in querying a Semantic Web simplifies the query sentence structure and removes the necessity of using variables from each query, which makes it much easier for users to query the Semantic Web. This framework provides query evaluation rules based on the proposed lexicographic semantics, which guarantees that each query using such a rich vocabulary is correctly evaluated over the underlying Semantic Web.