摘要
为了程序化地发现数据集间的语义关联,促进关联数据的开放共享。设计一种关联数据集的描述模型,并根据数据集描述特征,提出一种综合语义相似度的数据集关联发现方法。通过实验表明,该研究不仅能实现数据集基本描述层面的关联,而且能发现数据集内部实体间的语义关联。该方法可以跨数据集实现语义互联,提高数据信息的关联程度。
In order to discover semantic associations among datasets programmatically, the ｏpen and sharing of associated data can be promoted. In this paper, a description model of associated datasets was designed, and a dataset association detection method was proposed based on the characteristics of datasets description. Experiments show that the study can not only achieve the correlation of the basic description level of the dataset, but also discover the semantic association among the entities in the dataset. This method can realize semantic interconnection across datasets and improve the correlation degree of data information.
作者
龚振
范冰冰
Gong Zhen,Fan Bingbing(1.School of Computer, South China Normal University,Guangzhou 510631,Guangdong,Chin)
出处
《计算机应用与软件》
北大核心
2018年第8期83-86,185,共5页
Computer Applications and Software
基金
广东省重大科技专项(2016B030305003)
关键词
开放数据
关联数据
数据集描述
语义相似度
Ｏpen data
Associated data
Dataset description
Semantic similarity
