キャンパスオントロジーに基づく異種データ間の相関検出

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2021/11/01

タイトル(英語): Campus Ontology-Based Correlation Detection Among Heterogeneous Data Sets

著者名: 塚越　雄登（電気通信大学大学院 情報理工学研究科／国立研究開発法人産業技術総合研究所人工知能研究センター），江上　周作（国立研究開発法人産業技術総合研究所人工知能研究センター／電気通信大学大学院 情報理工学研究科），清　雄一（電気通信大学大学院 情報理工学研究科），田原　康之（電気通信大学大学院 情報理工学研究科），大須賀　昭彦（電気通信大学大学院 情報理工学研究科）

著者名(英語): Yuto Tsukagoshi (Graduate School of Informatics and Engineering, The University of Electro-Communications/Artificial Intelligence Research Center, The National Institute of Advanced Industrial Science and Technology), Shusaku Egami (Artificial Intelligenc

キーワード: ナレッジグラフ，オントロジー，相関分析，学内環境改善　　knowledge graph，ontology，correlation analysis，campus environment improving

要約(英語): For data-driven decision making, it is essential to build a data infrastructure that stores various data. Since various data are accumulated within organizations such as universities, companies, and local governments, integration of data in different contexts and cross-sectional analysis are issues. Knowledge graphs with a graphical structure that can flexibly change the schema are suitable for integrating heterogeneous data. In this study, we focused on a university campus as an example and proposed an ontology for various data such as lectures, buildings, purchasing, bicycle parking, and energy consumption. In particular, it has become easier to extract data across heterogeneous data collected within an organization by semantically linking dimensions with various expressions. Then, the collected unstructured data was accumulated as a knowledge graph based on the ontology, and the data infrastructure was constructed. In addition, we found several correlations through scenario-based experiment using this knowledge graph and showed the possibility that it could be applied to considering approach for university managemsent and improving the campus environment.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.141 No.11 （2021） 特集：電気関係学会関西連合大会

本誌掲載ページ: 1222-1233 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/141/11/141_1222/_article/-char/ja/