A study on suggestion of predicates using the clustering of item names for making RDF of Open Data

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  • CHEN Bo
    Graduate School of Science and Engineering, Kagoshima University
  • FUCHIDA Takayasu
    Graduate School of Science and Engineering, Kagoshima University
  • TOMARI Daiki
    Graduate School of Science and Engineering, Kagoshima University
  • HISANAGA Tadanori
    Graduate School of Science and Engineering, Kagoshima University

Bibliographic Information

Other Title
  • オープンデータのRDF化のための項目名のクラスタを使用した述語 のサジェストに関する研究
  • オープンデータ ノ RDFカ ノ タメ ノ コウモクメイ ノ クラスタ オ シヨウ シタ ジュツゴ ノ サジェスト ニ カンスル ケンキュウ

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Abstract

<p>　In recent years, there has been increasing interest in Open Data. The utilization of Open Data has been promoted, and many organizations including the national government, local governments and other organizations are working on publishing and utilizing Open Data. Open data of Kagoshima City has been published in July 2016 as CSV format. Under Open Data of local governments, even if they are disclosed due to the difference in data format and the lack of linkage of data, there is no active utilization yet. In this research, we focused on the vocabulary that corresponds to the predicate of RDF form for Open Data, and proposed a method to suggest predicates by the clustering of item names for RDF of Open Data as teacher signals of Deep Learning. Then, we presented results of the predicate suggestion.</p>

Journal

  • Joho Chishiki Gakkaishi

    Joho Chishiki Gakkaishi 30 (2), 236-241, 2020-05-23

    Japan Society of Information and Knowledge

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