The Analysis Of Ripple Effect For Ontology Evolution

With the development of the Semantic Web and the wide application of ontology concepts,the evolution of ontology has gradually become a relatively important research topic in the field of Semantic Web.By quantitatively evaluating the ripple effect of concepts or entities in the ontology,the ontology developer can evaluate and try to control the complexity of the ontology to ensure the usable properties of the ontology and the ontology user can accurately choose more applicable ontology data.At the same time the research of ontology evolution also plays an important role in promoting the development of semantic web and the development of knowledge sharing.The existing methods preliminarily quantify the ripple effect in the ontology,but not consider the influence of the semantic relationship for the ripple effect.Aiming at the problems existing in the research status and based on the existing research models,this paper proposes a quantitative evaluation method based on the TFOF(Term Frequency and Ontology Frequency)and applies it to ontology evolution research.The method uses the frequency of the semantic relationship in the ontology to calculate the weight of the relationship,so as to obtain the semantic relationship matrix corresponding to the ontology.Finally,the improved Floyd-Warshall algorithm is used to calculate the ripple effect of each concept or entity.Based on the evaluation model the TFOF,this paper analyzes the problem of low space utilization of the matrix storage and the time complexity of the floyd-warshall algorithm.This paper uses the SPFA(Shortest Path Faster Algorithm)based on the adjacency list to calculate the ripple effect,and the calculation algorithm of ripple effect in ontology evolution is proposed to improve the computational efficiency of ripple effect during the ontology evolution.The experimental results show that the evaluation method based on the TFOF ripple effect can more accurately measure the ripple effect of concepts or entities in the evolution process of ontology,And the improved method can computed the ripple effect faster then before.