【摘要】 采用改进的欧氏距离的检索算法解决区间特征属性的计算,并在此基础上解决案例模糊属性的相似度度量问题.采用PULL&PUSH调整策略,并主要采用GoodUpMatching(简称GUM)调整方法进行案例权重的调整.文章系统提出了一套案例检索及其权重优化方法.并以第三方电子集市的人力资源配置系统为实例,完成了该检索方法及权重优化方法的有效性和效率对比实验,验证了它的有效性及优化性.更多还原

【Abstract】 Based on calculation of range characteristic attribute by improving similarity algorithm based on Eulerian-Lagrangian Distance, the paper resolves similarity algorithm measure of fuzzy attribute of cases. The paper adjusts weight with PULL & PUSH tactics, especially GoodUpMatching(GUM for short) method. A method of case retrieval and optimal weight is proposed. Taking the HR deployment system base on the third-part e-marketplace as example, the paper tests the effectiveness of the system, the efficiency of retrieval method, the extent of adaptation and adaptation efficiency, effectiveness and optimality of the method is demonstrated.更多还原