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公开(公告)号:US07983926B2
公开(公告)日:2011-07-19
申请号:US11811175
申请日:2007-06-08
申请人: Iqbal Adjali , Malcolm Benjamin Dias , Wael El-Deredy , Carmen Maria Sordo-Garcia , Ming Li , Paulo Jorge Lisboa Gomes
发明人: Iqbal Adjali , Malcolm Benjamin Dias , Wael El-Deredy , Carmen Maria Sordo-Garcia , Ming Li , Paulo Jorge Lisboa Gomes
IPC分类号: G06Q10/00
CPC分类号: G06Q30/02 , G06Q10/06375 , G06Q10/06395 , G06Q30/0203 , G06Q30/0204
摘要: In an automated method for providing personalised recommendations to a user, a global probabilistic purchase model based on prior interactions of a group of users of a system, is used in the generation of personalised recommendations for future purchases for a given user. Attributes of the given user are used to identify characteristics relating to the user's personal purchasing, correction factors are calculated to update the output of the global probabilistic purchase model to personalise the recommendations for the user.
摘要翻译: 在用于向用户提供个性化建议的自动化方法中,基于系统的一组用户的先前交互的全局概率购买模型被用于为给定用户的将来购买生成个性化推荐。 给定用户的属性用于识别与用户个人购买相关的特征,计算校正因子以更新全局概率购买模型的输出以个性化用户的建议。
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公开(公告)号:US20080306808A1
公开(公告)日:2008-12-11
申请号:US11811175
申请日:2007-06-08
申请人: Iqbal Adjali , Malcolm Benjamin Dias , Wael El-Deredy , Carmen Maria Sordo-Garcia , Ming Li , Paulo Jorge Gomes Lisboa
发明人: Iqbal Adjali , Malcolm Benjamin Dias , Wael El-Deredy , Carmen Maria Sordo-Garcia , Ming Li , Paulo Jorge Gomes Lisboa
IPC分类号: G06Q30/00
CPC分类号: G06Q30/02 , G06Q10/06375 , G06Q10/06395 , G06Q30/0203 , G06Q30/0204
摘要: In an automated method for providing personalised recommendations to a user, a global probabilistic purchase model based on prior interactions of a group of users of a system, is used in the generation of personalised recommendations for future purchases for a given user. Attributes of the given user are used to identify characteristics relating to the user's personal purchasing, correction factors are calculated to update the output of the global probabilistic purchase model to personalise the recommendations for the user.
摘要翻译: 在用于向用户提供个性化建议的自动化方法中,基于系统的一组用户的先前交互的全局概率购买模型被用于为给定用户的将来购买生成个性化推荐。 给定用户的属性用于识别与用户个人购买相关的特征,计算校正因子以更新全局概率购买模型的输出以个性化用户的建议。
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