Application of a Novel Subject Classification Scheme for a Bibliographic Database Using a Data-Driven Correspondence

Frontiers in Big Data

Satoko Ando¹  Yuan Sun²  Kei Kurakawa³ 

[1] Clarivate Analytics (Japan), Co. Ltd., Tokyo, Japan;Information and Society Research Division, National Institute of Informatics, Tokyo, Japan;Scholarly and Academic Information Division, Cyber Science Infrastructure Development Department, National Institute of Informatics, Tokyo, Japan;

关键词: bibliographic database;    data-driven correspondence;    research project database;    subject classification scheme;    topological space;   

DOI  :  10.3389/fdata.2019.00048

来源: DOAJ

【 摘 要 】

A novel subject classification scheme should often be applied to a preclassified bibliographic database for the research evaluation task. Generally, adopting a new subject classification scheme is labor intensive and time consuming, and an effective and efficient approach is necessary. Hence, we propose an approach to apply a new subject classification scheme for a subject-classified database using a data-driven correspondence between the new and present ones. In this paper, we define a subject classification model of the bibliographic database comprising a topological space. Then, we show our approach based on this model, wherein forming a compact topological space is required for a novel subject classification scheme. To form the space, a correspondence between two subject classification schemes using a research project database is utilized as data. As a case study, we applied our approach to a practical example. It is a tool used as world proprietary benchmarking for research evaluation based on a citation database. We tried to add a novel subject classification of a research project database.

【 授权许可】

Unknown