摘要
基于CBR智能推荐系统是大型科学仪器协作共用网的重要组成部分。根据蚁群算法信息素更新原理设计并实现了一个完全异构案例集合构建策略。分析了完全异构案例集合构建原理,重点论述了案例权重动态分配的解决原理及过程。根据实验结果,表明该方法能够有效地提高智能推荐系统推荐结果的精确程度。
Based on CBR,the intelligent recommending system is the important part of scientific instrument shared network. According to pheromone updating theory of ant colony algorithm,this paper designs a constructive strategy of complete non-isomorphic case set and carries it out.In this paper,the complete non-isomorphic case set theory is analyzed and the principle and process of how to solve the dynamic distribution of case weight is discussed.The results of a experiment show that this method can efficiently enhance the accuracy of the results of intelligent recommending system
出处
《计算机工程与应用》
CSCD
北大核心
2008年第25期210-211,245,共3页
Computer Engineering and Applications
基金
云南省大型科学仪器
设备协作共用网及服务平台( No.2006PT06)
