IRST(k,l)-Index:一种支持分支路径查询的高效XML结构索引

IRST(k,l)-Index:an Efficient XML Structural Index for Branching Path Queries

为快速准确地查询图结构XML文档,本文在互关联后继树(IRST)的基础上,引入结构索引的相似性归并思想,提出一种基于互关联后继树且支持分支路径查询的高效XML结构索引—IRST(k,l)-index,并给出该索引的快速创建和查询算法.经实验验证,与国际上同类索引相比,该索引的创建速度更快、查询效率更高、空间开销更小.

To speed up queries over graph-structured XML documents, on the basis of Inter-Relevant Successive Trees （IRST）, we introduce the idea of similarity merging from structural index, and propose an efficient IRST-based structural index for branching path queries, IRST（k,l）-index. Moreover, its quick construction and query algorithms are presented. Compared with the same kind of indexes, experiments results show that IRST（k,l）-index performs more efficient in terms of space consumption and query performance, while using significantly less construction time.