Product configuration technology is an important method for implementing Mass Customization paradigm. It used to configure personalized products within a short period of time by maximal utilization of original production resources. In the configuration process for meeting user requirements, it is very possible to get several configuration results from a product family. So, how to select the optimal configuration result is an inevitable issue for manufacture. In the light of the problem, this study provides a recommendation strategy so as to improve the productivity and the resource utilization of manufactory. The strategy is represented by Algorithm Recommend. It is given to select the optimal result by analyzing and comparing the degree of similarity between the configuration results and the historical data in manufacture. The degree of similarity integrates the configuration logic and the tree structure characteristics by using the weighted method. The final example is a symbolic application which proves that this recommendation strategy can help efficiently to find the optimal configuration result for manufacture.

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