文章基本信息

标题：Text and Data Quality Mining in CRIS
本地全文：下载
作者：Otmane Azeroual
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2019
卷号：10
期号：12
页码：1-8
DOI：10.3390/info10120374
出版社：MDPI Publishing
摘要：To provide scientific institutions with comprehensive and well-maintained documentation of their research information in a current research information system (CRIS), they have the best prerequisites for the implementation of text and data mining (TDM) methods. Using TDM helps to better identify and eliminate errors, improve the process, develop the business, and make informed decisions. In addition, TDM increases understanding of the data and its context. This not only improves the quality of the data itself, but also the institution’s handling of the data and consequently the analyses. This present paper deploys TDM in CRIS to analyze, quantify, and correct the unstructured data and its quality issues. Bad data leads to increased costs or wrong decisions. Ensuring high data quality is an essential requirement when creating a CRIS project. User acceptance in a CRIS depends, among other things, on data quality. Not only is the objective data quality the decisive criterion, but also the subjective quality that the individual user assigns to the data.
关键词：current research information systems (CRIS); research information; text and data mining (TDM); data quality; knowledge exploration; knowledge transfer; decision making; user acceptance current research information systems (CRIS) ; research information ; text and data mining (TDM) ; data quality ; knowledge exploration ; knowledge transfer ; decision making ; user acceptance