ECTree: an extended tree index for attributed subgraph queries

Jun Luo, G. Butler
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Abstract

Graphs are popular data structures for modeling complex data types. There is a need for managing such graph data and providing efficient querying tools. In the graph mining realm, the problem lies in indexing a large number of graphs for fast retrieval. Indexing attributed graphs and using attributed queries can provide faster response time and results that are more refined. Our index technique ECTree focuses on extending an existing index to support attributed graph indexing and providing subgraph querying access to the extended index. The aim is to find a way such that the labels of the graphs as well as the attributes of the graphs are indexed at the same time. A query format is provided to query the extended index with flexibility on the attributes. In addition, regular expressions are used as query labels to provide flexibility. We also introduce a label-irrelevant vertex degree-attribute pruning method. All the techniques presented in our work are validated through experiments on both real and synthetic datasets.
ECTree:用于属性子图查询的扩展树索引
图是为复杂数据类型建模的流行数据结构。需要管理这些图形数据并提供有效的查询工具。在图挖掘领域,问题在于为快速检索而对大量图建立索引。索引属性图和使用属性查询可以提供更快的响应时间和更精细的结果。我们的索引技术ECTree侧重于扩展现有索引,以支持属性图索引,并提供对扩展索引的子图查询访问。目的是找到一种方法,使图的标签和图的属性同时被索引。提供了一种查询格式来查询扩展索引,在属性上具有灵活性。此外,正则表达式用作查询标签以提供灵活性。我们还引入了一种与标签无关的顶点度属性修剪方法。我们工作中提出的所有技术都通过真实和合成数据集的实验进行了验证。
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