Multi-view ontology alignment visualization (MOAV): A human-cognition based ontology alignment visualization technique

被引：0

作者：

Chen, Jie ^{[1
]}

Zhang, Jie ^{[2
]}

Xue, Xingsi ^{[3
,4
]}

Huang, Yikun ^{[5
]}

机构：

[1] Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, No.33 Xueyuan Road, University Town, Minhou, Fuzhou,Fujian,350118, China

[2] School of Computer Science and Engineering, Yulin Normal University, No.299 Education Middle Road, Yulin City,Guanxi Province,537000, China

[3] Fujian Provincial Key Laboratory of Big Data Mining and Applications Intelligent Information Processing Research Center, Fujian University of Technology, No.33 Xueyuan Road, University Town, Minhou, Fuzhou,Fujian,350118, China

[4] Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, No.1 Jinji Road, Guangxi, Guilin,541004, China

[5] Department of Information Technology, Concord University College, Fujian Normal University, No.68 Xueyuan Road, University Town, Minhou, Fuzhou,Fujian,350117, China

来源：

Journal of Network Intelligence | 2020年 / 5卷 / 04期

关键词：

Efficiency - Information systems - Benchmarking - Ontology;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

To further improve the quality of ontology alignment, it is necessary for an ontology matcher to introduce a user’s knowledge into its automatic matching process, which yields the development of interactive ontology matching techniques. Since validating problematic entity correspondences is a difficult cognition task, user interaction based on Ontology Alignment Visualization (OAV) has become the critical component of an interactive ontology matcher, which directly affects the quality of validating result and the efficiency of validating process. The existing OAV tools are mainly developed based on their designers’ subjective feelings and experiences, which do not take into consideration the law of human cognition. To improve the efficiency of the ontology alignment validating process, in this paper, a Multi-view OAV (MOAV) is proposed, which synthetically utilizes the human cognitive theory-information visualization and human-computer inter-action. The experiment utilizes the Ontology Alignment Evaluation Initiative (OAEI)’s benchmark to test the performance of our proposal, and the experimental results show that MOAV can effectively improve a user’s validating efficiency. © 2020, Taiwan Ubiquitous Information. All rights reserved.

引用

页码：198 / 210