On the Move to Meaningful Internet Systems: OTM 2009
On the Move to Meaningful Internet Systems: OTM 2009
复制标题
迈向有意义的互联网系统：OTM 2009
DOI：
10.1007/978-3-642-05151-7_27
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Salvadores M
中科院分区：
文献类型：
--
作者：
Salvadores M
语义网所支持的开放数据的持续趋势已经开始产生大量的数据源。这些数据源是使用RDF词汇表发布的，并且由于它们的图形拓扑，可以在整个数据中导航。本文提出了一种基于LinksB2N的RDF数据集成算法，该算法能够在不需要人工干预的情况下发现RDF数据库中的信息重叠，并在不同的置信度下从不同的数据集中识别出等价的RDF资源。该算法依赖于一种新的方法，使用聚类技术来分析不同数据图中包含重叠信息的唯一对象的分布。我们的贡献是说明在市场混合洞察项目的背景下，通过应用LinksB2N算法的数据集的顺序数以亿计的RDF三元组包含相关信息的企业对企业（B2B）的营销分析领域。
The ongoing trend towards open data embraced by the Semantic Web has started to produce a large number of data sources. These data sources are published using RDF vocabularies, and it is possible to navigate throughout the data due to their graph topology. This paper presents LinksB2N, an algorithm for discovering information overlaps in RDF data repositories and performing data integration with no human intervention over data sets that partially share the same domain.LinksB2N identifies equivalent RDF resources from different data sets with several degrees of confidence. The algorithm relies on a novel approach that uses clustering techniques to analyze the distribution of unique objects that contain overlapping information in different data graphs. Our contribution is illustrated in the context of the Market Blended Insight project by applying the LinksB2N algorithm to data sets in the order of hundreds of millions of RDF triples containing relevant information in the domain of business to business (B2B) marketing analysis.