Mining Configuration Rules for Personalized Product Customization
With the aim of acquiring tacit configuration rule knowledge in personalized product configuration,the association mining method is used to infer tacit configuration rule knowledge such that personalized recommendation to customers can be made in the configuration process.With the historical sales data of products,a bi-level genetic algorithm with the rule coding representa-tion and corresponding operators is proposed to obtain the association rules.The effectiveness of the presented approach is illustrated by a case study on tablet computers.Experiments demonstrate that,compared with the Apriori algorithm,the proposed method can adaptively obtain the threshold of rule support and confidence,and thus avoid the shortcomings of Apriori method in manually set-ting a threshold for rule support and confidence.As a result,the tacit rule knowledge in product configuration can be effectively ob-tained to facilitate the process of product customization and recommendation.
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