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A hybrid recommendation system for E-commerce based on product description and user profile

机译:基于产品描述和用户配置文件的电子商务混合推荐系统

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E-commerce is an online trading system that eases transactions for both sellers and consumers without having to meet in person. The prevalence of e-commerce has increased competition amongst sellers, hence the users of e-commerce has to increase their performance, one of them by using recommendation system. This research develops a hybrid recommendation system for e-commerce that implements Content-based Filtering and Collaborative Filtering methods, which will compute the simmilarities of product description and user profile. In experiment results, it was found that the recommendation has similarity with product description and the preference of user profile with the average of precision value is 67.5% and recall value is 71.47%.
机译:电子商务是一个在线交易系统,可以在不必亲自见面的情况下减轻卖家和消费者的交易。电子商务的普遍率增加了卖方之间的竞争,因此电子商务的用户必须通过使用推荐系统来提高他们的性能,其中一个。本研究开发了一种用于电子商务的混合推荐系统,实现基于内容的过滤和协作过滤方法,这将计算产品描述和用户简档的酶促性。在实验结果中,发现该建议具有与产品描述的相似性,并且用户简档的偏好具有平均值的平均值为67.5 %,召回值为71.47 %。

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