摘要
针对目前本体匹配算法存在运行效率低和匹配准确度不高等问题,提出一种基于人工免疫的动态本体匹配算法,用来快速地从现有本体中筛选出用户所需的子本体。该算法根据用户行为信息构建抗原本体模型,利用情景匹配确定其领域上下文环境,然后通过结构匹配获得匹配度最高的本体,最后对本体执行语义匹配得到最终需要的子本体。实验表明,该算法提高了本体匹配的准确度和效率。
Because of the low efficiency and low accuracy existing in the traditional ontology matching algorithms, we introduce an automatic ontology matching algorithm based on artificial immunity to rapidly get the required sub-ontology from the existing ontology pool. The algorithm constructs an antigen ontology model according to the information of users＇ behaviors, determines its domain context by matc- hing the context, obtains the ontology with the highest matching degree via structure matching, and finally gets the right ontology through semantic matching. The experimental results show that the algorithm can improve the precision and the efficiency of ontology matching.
出处
《计算机工程与科学》
CSCD
北大核心
2015年第6期1127-1134,共8页
Computer Engineering & Science
基金
江苏省产学研联合创新资金资助项目(SBY201320423)
关键词
本体匹配
抗原本体
情景匹配
结构匹配
语义匹配
ontology matching
antigen ontology
context matching
structure matching
semanticmatching
