Abstract: As a crucial point of semantic integration，ontology mapping is researched in-depth at home and abroad.The machine learning method is introduced to weights computing in combining concept similarities，and the weight allocation algorithm LMSW based on Widrow-Hoff theory is proposed.In LMSW，the weight vector most fitting the training samples is searched by gradient descent method，so that the final combined concept similarity can be attained，and the ontology mapping which combines multiple concept similarity strategies can be determined eventually.Experiment indicates that the method performs well in improving precision and recall compared to individually using other algorithms.

Key words: ontology mapping, concept similarity, weight allocation

摘要： 本体映射是语义集成的关键，国内外对本体映射进行了深入的研究。将机器学习的方法引入到组合概念相似度的权值计算中来，提出了基于Widrow-Hoff理论的权值确定算法LMSW。通过梯度下降法来搜索最佳拟合训练样例的权向量，从而计算出组合的概念相似度，最终实现组合多种概念相似度算法的本体映射。实验表明该算法比单独使用概念相似度计算方法在查全率、查准率上均有所提高。

关键词: 本体映射, 概念相似度, 权值分配