MultiGraphMatch：一种面向多重图的子图匹配算法
MultiGraphMatch: a subgraph matching algorithm for multigraphs
AI总结：
针对多重图子图匹配研究不足的问题，提出MultiGraphMatch算法，采用位矩阵索引与基于可匹配边基数的查询边排序技术，支持CYPHER带逻辑条件查询，在多类图数据上性能优于或持平于现有方案。
摘要：
子图匹配是在称为目标图的更大规模图中，找出称为查询图的小型图所有出现位置的问题。尽管该问题在简单图中已得到广泛研究，但针对多重图（两个节点间可存在多条边，每条边代表一种可能不同的关系类型）的解决方案仍十分有限。在我们提出的新算法MultiGraphMatch中，节点和边均可关联标签与多种属性。MultiGraphMatch引入了名为位矩阵（bit matrix）的新型数据结构，可高效为查询图和目标图建立索引，并筛选出与每条查询边可匹配的目标边集合。此外，该算法还提出了一种基于可匹配边集合基数对查询边处理顺序进行排序的新技术。借助CYPHER查询定义语言，MultiGraphMatch可执行带有节点和边标签逻辑条件的查询。我们将MultiGraphMatch与SuMGra以及图数据库系统Memgraph、Neo4J进行了对比，结果表明在各类合成图与真实世界图的所有查询任务中，该算法性能均达到可比水平或更优。
英文摘要：
Subgraph matching is the problem of finding all the occurrences of a small graph, called the query, in a larger graph, called the target. Although the problem has been widely studied in simple graphs, few solutions have been proposed for multigraphs, in which two nodes can be connected by multiple edges, each denoting a possibly different type of relationship. In our new algorithm MultiGraphMatch, nodes and edges can be associated with labels and multiple properties. MultiGraphMatch introduces a novel data structure called bit matrix to efficiently index both the query and the target and filter the set of target edges that are matchable with each query edge. In addition, the algorithm proposes a new technique for ordering the processing of query edges based on the cardinalities of the sets of matchable edges. Using the CYPHER query definition language, MultiGraphMatch can perform queries with logical conditions on node and edge labels. We compare MultiGraphMatch with SuMGra and graph database systems Memgraph and Neo4J, showing comparable or better performance in all queries on a wide variety of synthetic and real-world graphs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
