A Compact Hybrid Evolutionary Algorithm for Large Scale Instance Matching in Linked Open Data Cloud

作者：Xue, Xingsi^*; Liu, Jianhua

来源：International Journal on Artificial Intelligence Tools, 2017, 26(4): 1750013.

DOI：10.1142/S0218213017500130

• Compact hybrid evolutionary algorithm
• linked open data cloud
• large scale instance matching

Establishing correct links among the coreference ontology instances is critical to the success of Linked Open Data (LOD) cloud. However, because of the high level heterogeneity and large scale instance set, matching the coreference instances in LOD cloud is an error prone and time consuming task. To this end, in this work, we present an asymmetrical profile-based similarity measure for instance matching task, construct new optimal models for schema-level and instance-level matching problems, and propose a compact hybrid evolutionary algorithm based ontology matching approach to solve the large scale instance matching problem in LOD cloud. Finally, the experimental results of comprising our approach with the states of the art systems on the instance matching track of OAEI 2015 and real-world datasets show the effectiveness of our approach.

• 出版日期2017-8
• 单位福建工程学院