基于语义网和遗传算法的知识图形化展示研究

Study of knowledge graphical display based on semantic Web and genetic algorithm

为提升领域知识认知、解读的效率,以现有技术为基础,进一步研究了知识的图形化展示方法。基于本体和语义网技术讨论了适用于图形化展示的知识模型和相应展示方案。针对知识图布图问题,基于遗传算法,研究了目标函数、对编码方案进行了优化、引入了优势解保留的精英解群,并改进了遗传策略。算例对比证明,该算法能够在减少交叉点的同时达到聚类目的,效率较高。以上研究的知识模型和布图算法可用于实际系统,并为类似研究提供参考。

For improving the cognitive and reading efficiency of domain knowledge,on the basis of the existing technology,this paper further studied the method of graphical display of knowledge.Based on ontology and semantic Web technology,it discussed the basic knowledge model and corresponding exhibition proposal which could be used to graphical display.Pointing to the layout problem of the knowledge graph,based on the genetic algorithm,combined with the actual layout requirements,it studied the suitable objective function,optimized the coding scheme,and also introduced the elite solutions group technology for saving advantage solutions.At the same time,it also improved the genetic strategy according to above processing characteristics.Example comparison proves the algorithm can reduce the intersections and achieve clustering purpose,has high efficiency,and can be used in the actual application.The above knowledge model and layout algorithm can be used in the actual system,and provide reference for similar research.