一种改进的蚁群算法在知识路由系统中的应用

An Improved Ant Colony Algorithm for Knowledge Routing System

语义Web上分布着海量知识,如何在这些海量知识中按照用户的需求快速准确地定位目标知识便成为知识路由研究中亟待解决的问题。针对此问题,应用了蚁群算法作为动态虚拟语义社区中的知识路由算法,并对算法的选择策略、信息素修改两个方面进行改进,使算法不易陷入局部最优解,并能快速收敛到全局最优解。实验结果表明其路由效率明显提高,具有较好的性能。

There is a large amount of knowledge in the Semantic Web, so one critical issue on how to effectively locate the knowledge is necessary to be handled with according to the requirement of user. This paper presents a routing strategy based on Ant Colony Algorithm （ACA） in virtual semantic community. And it is improved in two parts, including selection strategy and pheromone modification so that a local optimal solution is not gotten and a global optimal solution is gotten quickly through convergence. The result shows that the algorithm gains a good performance.