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Hybrid collaborative filtering for high-involvement products: A solutionn to opinion sparsity and dynamics

机译:高参与度产品的混合协作过滤:意见稀疏性和动态性的解决方案

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摘要

High capital value goods that are purchased only after long and careful consideration, such as a car, truck, appliance (called high-involvement products) are increasingly being purchased online. For these products accurate recommendations are very important. Collaborative filtering (CF) is a commonly used approach for recommending products based on known preferences of similar users. Two challenges that limit the performance of CF in high-involvement products are the ratings' sparsity and dynami
机译:仅在经过长时间和仔细考虑之后才购买的高资本价值商品,例如汽车,卡车,家用电器(称为高参与性产品),越来越多地在网上购买。对于这些产品,准确的建议非常重要。协作过滤(CF)是一种基于相似用户的已知偏好来推荐产品的常用方法。限制CF在高参与度产品中的性能的两个挑战是等级的稀疏性和动态性

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