FROG: Inference from knowledge base for missing value imputation

• DOI: 10.1016/j.knosys.2018.01.005
• Publication Date: 2018-01-03T22:07:29Z
• Authors: Zhixin Qi; Hongzhi Wang; Jianzhong Li; Hong Gao
• Keywords: Imputation (statistics)

Abstract Data imputation is a basic step for data cleaning. Traditional data imputation approaches are lack of accuracy in the absence of knowledge. Involving knowledge base in imputation could overcome this shortcoming. A challenge is that the missing value could be hardly found directly in the knowledge bases (KBs). To use knowledge base sufficiently for missing value imputation, we present FROG, an in f erence algo r ithm from kn o wled g e bases. The inference not only makes full use of true facts in KBs, but also utilizes types to ensure the accuracy of captured missing values. Extensive experiments show that our proposed algorithm can capture missing values efficiently and effectively.