LOD conversion system for generating large knowledge base from web contents
LOD conversion system for generating large knowledge base from web contents
复制标题
用于从网页内容生成大型知识库的 LOD 转换系统
DOI：
10.1109/gcce.2017.8229390
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Noboru Sonehara
中科院分区：
文献类型：
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作者：
Kazuki Takahashi;Toshitaka Maki;Toshihiko Wakahara;Toru Kobayashi;Akihisa Kodate;Noboru Sonehara
近年来，关联开放数据（LOD）作为构建语义Web的技术受到了国际上的广泛关注。LOD基于资源描述框架（RDF）创建，并考虑语义关系将每个资源链接起来。但是，LOD存在资源之间的链接不够，创建LOD需要大量的时间等问题。因此，本文提出了一种新的LOD转换系统，可以将Web内容转换为LOD。该系统使用DBpedia LOD从Web内容中的句子中提取关键词，并生成知识库。实验结果表明，该系统能够以2.03秒/页的速度将目标网页完全转换为RDF数据。此外，系统还利用DBpediaLOD实现了通过对资源的概念进行估计来生成知识库。LOD中的链接数量增加了2.0倍，超过了未估计的RDF数据。
In recent years, the Linked Open Data (LOD) have been attracting attention in the world as the technology that can construct the semantic Web. The LOD are created based on the Resource Description Framework (RDF), and can link each of resources considering semantic relations. However, there are problems that the LOD do not have enough links between resources, and the LOD need a lot of time for creation. Therefore, this paper presents the new LOD conversion system that can convert the Web contents to the LOD. This system extracts keywords from sentences in the Web contents using DBpedia LOD, and generates the knowledge base. By experiments, the proposed system was confirmed that it can convert the target Web pages to the RDF data fully at 2.03 seconds per a page. In addition, the system realized to generate the knowledge base by estimating the concepts of the resources using the DBpedia LOD. The number of links in the LOD is increasing 2.0 times and more than non-estimated RDF data.