Abstract: An improved intelligent Component Retrieval Model based on genetic algorithm with Facet-Weight Self-learning （CRMFWS） is proposed in this paper.Genetic algorithm based facet weight self-learning algorithm can change the facet weight dynamically in order to improve retrieval accuracy，and risk minimization-based component sampling algorithm is used to solve the insufficiency of training data.The experimental results prove that this algorithm is feasible and can improve component retrieval efficiency greatly.

摘要： 提出了一种改进的基于遗传算法的刻面权重自学习构件检索模型（CRMFWS），采用基于刻面权重自学习的遗传算法来动态地改变刻面权重以提高查准率；采用基于构件采样的风险最小化算法来解决训练数据不充分问题。实验结果表明该算法是可行的，能够大幅度提高构件的检索效率。