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Modeling for Comment Trust Recommendation Based on Collaborative Filtering

机译:基于协同过滤的评论信任推荐建模

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Asymmetry in the parties of the transaction leads to uncertainty in the transaction. Trust problem has been one of the bottlenecks restricting the development of ecommerce. For e-commerce product review issues, comment trust recommendation model was proposed based on comment credibility degree and user similarity, which combined with social networking trust mechanism and collaborative filtering to offer users with a more personalized trust recommendations. The experimental results demonstrate that the model can effectively improve the recommendation accuracy and solve cold startup problems in collaborative filtering.
机译:交易各方的不对称导致交易中的不确定性。信任问题是限制电子商务发展的瓶颈之一。对于电子商务产品审查问题,根据评论信誉程度和用户相似性提出了评论信任推荐模型,这些模型与社交网络信任机制和协作过滤相结合,为用户提供更个性化的信任建议。实验结果表明,该模型可以有效地提高建议准确性和协同滤波中的冷启动问题。

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