计算机工程2019，Vol.45Issue(3)：14-19,6.DOI:10.19678/j.issn.1000-3428.0052715
多策略自适应大规模本体映射算法
Multi-strategy Adaptive Large-scale Ontology Mapping Algorithm
摘要
Abstract
Large-scale ontology mapping in the context of large data has high time complexity, low efficiency and accuracy.Therefore, a multi-strategy adaptive large-scale ontology mapping algorithm based on modularity and local confidence is proposed.Clustering and modularizing the inner part of the system, discovering the correlated sub-ontologies with high similarity between modules based on information retrieval strategy, calculating the local confidence under each mapping strategy among the correlated sub-ontologies, and adjusting the weight of the corresponding strategy adaptively based on the local confidence when combining the mapping results.On this basis, heuristic greedy strategy is used to extract mapping results and correct them based on mapping rules.Experimental results show that compared with Falcon and ASMOV methods, the proposed algorithm has higher recall, precision and F-measure value.关键词
大数据/大规模本体映射/模块化/局部置信度/自适应Key words
big data/large-scale ontology mapping/modularity/local confidence/self-adaption分类
信息技术与安全科学引用本文复制引用
蒋猛,禹明刚,王智学..多策略自适应大规模本体映射算法[J].计算机工程,2019,45(3):14-19,6.基金项目
国家自然科学基金(61802428). （61802428）
