知识图谱压缩及查询算法研究  

Research on Compression and Query Algorithm of Knowledge Graph

作　　者：张伟娟 韩斌[1] ZHANG Wei-juan;HAN Bin(School of Computing,Jiangsu University of Science and Technology,Zhenjiang 212003,China)

机构地区：[1]江苏科技大学计算机学院,江苏镇江212003

出　　处：《软件导刊》2022年第11期82-87,共6页Software Guide

摘　　要：针对知识图谱数据规模过大、查询时载入时间过久等问题,从知识图谱的压缩方向提出等价关系的压缩算法CER。该方法先判断知识图谱的边标签是否相同,再判断节点标签的属性值,根据不同情况压缩边标签并划分顶点集。该压缩算法减少了知识图谱的空间规模,从而在一定程度上提高了查询效率。最后,针对3个公开的知识图谱数据集进行4种压缩算法的对比实验,从边和节点的压缩率、压缩时间以及基于PLL索引算法的查询时间进行比较,验证了该算法压缩效果较好。Aiming at the problem of too large data scale of the knowledge graph and too long loading time when querying,a compression algorithm CER(Compression based on Equivalence Relation)is proposed from the compression direction of the knowledge graph. This method first judges the edge label of the knowledge graph Whether they are the same,then determine the attribute value of the node label,compress the edge label and divide the vertex set according to different situations. The compression algorithm reduces the spatial scale of the knowledge graph,thereby improving the query efficiency to a certain extent. Finally,a comparative experiment of four compression algorithms is carried out for three public knowledge graph data sets,and the effect of this algorithm is verified from the compression ratio of edges and nodes,compression time,and query time based on the PLL index algorithm,which proved the proposed algorithm has better compression effect.

关 键 词：知识图谱 压缩算法 边标签 节点标签 PLL索引算法 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]