Return
Knowledge graph quality control: A survey
DOI:10.1016/j.fmre.2021.09.003.png)
Abstract
En 中文
A knowledge graph (KG), a special form of semantic network, integrates fragmentary data into a graph to support knowledge processing and reasoning. KG quality control is important to the utility of KGs. It is essential to inves-tigate KG quality and the parameters influencing KG quality to better understand its quality control. Although many works have been conducted to evaluate the dimensions of KG quality, quality control of the construction process, and enhancement methods for quality, a comprehensive literature review has not been presented on this topic. This paper intends to fill this research gap by presenting a comprehensive survey on the quality control of KGs. First, this paper defines six main evaluation dimensions of KG quality and investigates their correlations and differences. Second, quality control treatments during KG construction are introduced from the perspective of these dimensions of KG quality. Third, the quality enhancement of a constructed KG is described from various dimensions. This paper ultimately aims to promote the research and applications of KGs.
Keywords:
Knowledge graph
Quality control
Quality evaluation
Quality enhancement
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.3
Papers:
1.3K
Citations:
2.6K

