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E-COMMERCE CROSS-SAMPLING PRODUCT RECOMMENDER BASED ON STATISTICS
E-COMMERCE CROSS-SAMPLING PRODUCT RECOMMENDER BASED ON STATISTICS
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机译：基于统计的电子商务交叉抽样产品推荐
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摘要
A method of recommending products during e-commerce. A computing device including a processor implements a cross sampling recommender algorithm which includes a first statistical model is provided at a website. Responsive to receiving information via the Internet from a first customer including selection of a first product offered at the website, the algorithm automatically divides historical customer' selection information into a plurality of time ordered sub-periods of time. Using the customer' selection information and the time ordered sub-periods of time as a time covariate, logistic regressions are fit to each of a plurality of cross-sampled pairs of the plurality of products involving the first product. Using the data from the logistic regressions, cross-sampled pairs are identified which meet a slope selection criteria. A recommendation to the first customer for at least a first recommended product from the cross-sampled pairs is provided from cross-sampled pairs which meet the slope selection criteria.
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