Abstract: So far, the international community has only proposed an assessment metric for the extension conciseness of knowledge graph, but has not provided a standardized assessment method and process. To address this issue, the assessment method of the extension conciseness of knowledge graph is studied and a new method to assess the extension conciseness of the Chinese English mixed knowledge graph is proposed. The formulas for grouping at the overall level and assessing the head entities, relations, and tail entities are proposed and defined. To enhance the accuracy of the evaluation, the sentence level assessment formula is also defined. Finally, the four formulas are combined to create an algorithm for assessing the extension conciseness of the knowledge graph. To verify the accuracy and performance of the proposed algorithm, the open data set OPEN KG( Knowledge Graph) is used to assess and compare the proposed algorithm with related algorithms. The results confirm that the proposed algorithm provides a certain guarantee for the accuracy and time efficiency of the conciseness assessment of the Chinese English mixed knowledge graph, and the overall performance of the proposed algorithm is better than that of the related algorithm. 

Key words: data quality, quality dimension, extension conciseness, knowledge graph, knowledge graph quality evaluation