Deleting Method on Duplicated Recommending Commodities Based on Shopping Records of Users

Mengyuan Li, Jialin Ma, Alasdair Ivens


Leading e-commerce websites typically now have commodity recommendation functionality. Most users will notice that their recommendation list will contain the commodities purchased previously, despite them no longer need the item. Aimed at resolving this situation, a model has been developed which is able to remove such duplicated recommendations. This paper provided a series of comprehensive optimization schemes to delete duplicated items, based on previous filtering schemes, to include in any repurchase cycle.


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