Keyword Proximity Search over Large and Complex RDF Database

Zhen Niu, Haitao Zheng, Yong Jiang, Shutao Xia, Hui-Qiu Li
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引用次数: 2

Abstract

In this paper, we propose a keyword proximity search approach that can be applied to large and complex RDF database. We model RDF database as undirected data graph, construct three indexes for each data graph, only one index need be loaded into memory. Keyword graph is defined as search result, keyword tree and minimal keyword tree are proposed as middle structures for Keyword graph extraction, and we present a link join operation based algorithm to retrieve Keyword trees in this paper. We employ a technique of keyword node pruning to accelerate keyword tree retrieval and define a scoring function to rank search results. In experiments, our approach achieves both high efficiency and high accuracy, outperforms the existing approaches.
大型复杂RDF数据库的关键字邻近搜索
本文提出了一种适用于大型复杂RDF数据库的关键字接近搜索方法。我们将RDF数据库建模为无向数据图,为每个数据图构造三个索引,只需要将一个索引加载到内存中。本文将关键字图定义为搜索结果,提出了关键字树和最小关键字树作为关键字图提取的中间结构,并提出了一种基于链接连接操作的关键字树检索算法。我们采用关键字节点修剪技术来加速关键字树的检索,并定义了一个评分函数来对搜索结果进行排序。在实验中,我们的方法达到了高效率和高精度,优于现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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