基于属性权重的链接数据共指关系构建

Property Weight Based Co-reference Resolution for Linked Data

来自异构数据源的语义数据集之间关联的缺失严重影响了数据网的构建和发展。语义数据集中,实例数据之间共指关系的发现和构建能够丰富数据集之间的关联,从而有助于在数据集之间进行推理和查询。在基于相似度分析的共指关系构建的过程中,实例属性的权重及属性值的相似度对实例相似度具有重要作用。提出一种新的基于数据集统计信息计算属性权重的模型,并从概率统计的角度证明其合理性。同时分析了这种权重计算模型相对于传统的权重计算方法的优势。基于新的权重计算方法,实现了共指关系构建系统,并利用开放的语义数据集验证了其正确性。

The construction and development of the Web of data are affected seriously by the loss of Iinks amongseman tic datasets fromheterogeneousdata sources. The construction of co-reference between instances in semantic datasets will be helpful for enriching the links among datasets, which will improve the reasoning and query across datasets. The prop- erty weights and the similarities of property values play an important role in the co-reference resolution based on simi- larity analysis. This paper proposed a new model for obtaining the weights of properties from the statistical information of datasets, and proved its rationality theoretically. Furthermore, the advantages of this model compared with traditional method were analyzed. Based on the new method proposed by this paper, a system for building co-reference among se- mantic datasets was implemented, and the performance was verified with some open datasets.