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中文摘要：
随着语义网技术的标准化,网络上的关联数据爆炸式增长.海量的关联数据在网络上存储和交换变得越来越困难.本文提出了一种高密度关联数据压缩方案,将关联数据的三维关系矩阵分解成3个二维稀疏矩阵,再用K2-Tree压缩二维稀疏矩阵,提高了关联数据的压缩率和压缩效率.实验表明,本文提出压缩方案的压缩率相较于HDT＋＋平均有12%的提高,压缩耗时相较于HDT＋＋也有10%左右的降低.
英文摘要：
With the standardization of the semantic web technology, the linked-data is widely used in various fields, and grows explosively. The storage and exchange of mass linked-data on Internet become more and more difficult. In this paper, a high density compression method of linked-data is proposed, which splits three-dimensional matrix into three two-dimensional matrix and using K2-tree to compress the two-dimensional matrix. The experimental results show that the compression method proposed in this paper improves the compression rate by average 12% and the compression efficiency by average 10 % compared with HDT＋＋.
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