摘要
为更加高效、准确地对数据完整性进行评估,通过对国内外完整性评估技术和方法的研究,本文基于Linked data的数据特点,提出了用于数据完整性评估的β算法和用于隐含数据挖掘的Dam算法,并从理论上分析证明了算法的有效性和准确性。最后,将东北石油大学教务数据发布为Linked data作为验证数据进行实验,与文献中两种完整性评估算法进行了比对,结果表明:评估完整性提高约6%,评估效率平均提高约40倍,验证了本文算法的准确性和高效性。本文提出的基于Linked data的数据完整性评估算法不仅能保证数据评估的准确性,同时能大幅度提高计算效率。
In order to assess data integrity more efficiently and accurately,the existing technologies and methods for data integrity assessment are investigated. Then according to the data characteristics of Linked Data,two kinds of algorithms are proposed,the one is β algorithm for data integrity assessing,the other one is Dam algorithm for implicit data mining. Third,the effectiveness and accuracy of the algorithms are proved by theoretical analysis. Finally,the educational administration data is published to Linked Data.The β algorithm is compared with two kinds of integrity assessing algorithms in literature on the Linked Data published. The results show that the β algorithm improves the integrity for about 6%,and the efficiency increases about 40 times on average. The accuracy and efficiency of the proposed algorithm are verified. The data integrity assessment algorithm based on Linked Data proposed in this paper can not only ensure the accuracy of data evaluation,but also greatly improve the computational efficiency.
作者
袁满
胡超
仇婷婷
YUAN Man;HU Chao;QIU Ting-ting(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,China)
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2020年第5期1826-1831,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
黑龙省教育厅国家基金培育项目(2017PYYL-06)
黑龙江省哲学社会科学研究规划项目(19EDE334)
研究生创新基金项目(JYCX_CX07_2018_2)。
