摘要
语义推理的功能使得知识库更具人工智能,具有实用意义。文章根据语义模型的特点,构建了基于关系数据库的知识库语义存储体系,该存储体系的模式空间和实例空间相分离,降低了结构和数据的耦合性,使语义的存储范围更具完整性、语义的推理效果更具智能性。面向该存储体系的语义推理方法实现了相关语义(专家知识)的推理和相似语义(词汇)的推理,同时,该方法也考虑到了推理范围的可控能力和推理结果的语义还原能力。分析表明,该方法能应用于实际,但仍存在一些可改进之处。
Semantic reasoning makes the knowledge base more artificially intelligent, and has practical significance. A semantic storage system is constructed based on relational database, according to the characteristics of semantic model. The separation of the model-space and the instance-space makes the coupling between structure and data reduce, the semantic storage more complete and the effect of the reasoning more intelligent. The relevant reasoning （expert knowledge） and similar reasoning（vocabulary） are realized by semantic reasoning method for the storage system realizes. At the same time, the method takes into consideration the controllability of reasoning-range and semantic-recovering ability of reasoning results. The method can be applied practically, but there is space to get improved.
出处
《计算机时代》
2013年第7期48-51,共4页
Computer Era
基金
2012年浙江省现代远程教育学会课题(DES-12Y43)
关键词
推理
语义
模式空间
实例空间
知识库
关系数据库
semantic
reasoning
model-space
instance-spasce
knowledge base
relational database
