Commodity recommendations of retail business based on decisiontree induction

Collaborative filtering is an extensively adopted approach for commodity recommendation. This investigation presents a collaborative filtering method to support commodity recommendation of retail business according to customer preferences. Moreover, a novel recommendation methodology based on decision tree induction is also proposed to obtain further effectiveness and quality of recommendations. Effectiveness of the proposed method is evaluated by implementing a recommender system based on data mining and analyzing real retail business data to demonstrate the operability of the system.

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