基于滑动窗口的流式RDF数据的模式匹配方法
Pattern matching for streaming RDF graph over sliding windows
王翔1
作者信息
- 1. 北京科技大学 信息化建设与管理办公室,北京 100083
- 折叠
摘要
数据在社交网络中通常呈现为流式的特征.针对流式RDF数据,提出一种增量的模式匹配方法.设计一种面向RDF数据的索引结构,被定义为顶点聚簇的数据子图.提出一种基于顶点-边标签映射的有效验证的匹配算法,减少遍历过程中候选数据规模.实验结果表明,该方法在环状和星状查询图的模式匹配算法效率更具时间优势.
Abstract
Data is emerged as a streamlined feature in social networks.Regarding the streamlined feature of RDF data,an incre-mental method of pattern matching for streaming RDF graph was proposed.A specified data model for RDF data was given and it was defined as a vertex-clustered data subgraph(SGD).A matching algorithm based on valid verification of vertex-edges label mapping(ORCTM-PR)was proposed.The quantity of candidate data in traversal processing was effectively reduced.Experi-mental results show that the method provides better benefits than relational methods for cycle and star queries.
关键词
数据流/模式匹配/数据子图/数据索引/顶点聚簇/候选验证/增量匹配算法Key words
datastream/pattern matching/data graph/data index/vertex clustering/candidate verification/incremental matc-hing algorithm引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据