DETERMINING A LIKELIHOOD OF SUITABILITY BASED ON HISTORICAL DATA
    1.
    发明申请
    DETERMINING A LIKELIHOOD OF SUITABILITY BASED ON HISTORICAL DATA 审中-公开
    根据历史数据确定适应性的特征

    公开(公告)号:US20120030060A1

    公开(公告)日:2012-02-02

    申请号:US13192576

    申请日:2011-07-28

    IPC分类号: G06Q30/00 G06F15/18

    CPC分类号: G06Q30/02 G06Q30/0631

    摘要: Some embodiments of the invention determine whether a particular item is likely to suit a consumer from a fit and/or style standpoint, using objective data produced as a result of the consumer's experiences. For example, some embodiments of the invention analyze information regarding a consumer's experiences with certain products (e.g., purchase and return history, identification of “favorite” items, etc.) and data regarding attributes of those items (e.g., technical dimension data, stylistic and fit attributes, etc.) to determine the consumer's measurements and fit and/or style preferences, so that a prediction may be made regarding how a particular size of an item may suit the consumer.

    摘要翻译: 本发明的一些实施例使用根据消费者体验的结果产生的客观数据来确定特定物品是否可能从适合和/或风格的角度适合消费者。 例如,本发明的一些实施例分析关于某些产品的消费者体验的信息(例如,购买和退货历史,“喜爱”项目的识别等)以及关于这些项目的属性的数据(例如,技术维度数据,风格 和适合属性等)以确定消费者的测量和适合度和/或风格偏好,使得可以对项目的特定尺寸如何适合消费者进行预测。

    FIT RECOMMENDATION VIA COLLABORATIVE INFERENCE
    2.
    发明申请
    FIT RECOMMENDATION VIA COLLABORATIVE INFERENCE 有权
    FIT通过协作式推荐建议

    公开(公告)号:US20120030061A1

    公开(公告)日:2012-02-02

    申请号:US13192617

    申请日:2011-07-28

    IPC分类号: G06Q30/00

    CPC分类号: G06Q30/0631 G06Q30/00

    摘要: Some embodiments of the invention provide techniques for recommending a size of a subject item to fit a subject consumer. In some embodiments, clusters of consumers with fit characteristics similar to the subject consumer are identified, using one or more data clustering algorithms, based on any of numerous consumer attributes (e.g., self-reported and/or inferred height, weight, body shape, body characteristics, and/or purchase histories (e.g., consumers with high overlap in terms of sets of products purchased)). Information on other consumers in the cluster may be analyzed to draw conclusions on how different sizes of the subject item may fit the subject consumer. For example, the purchase history of other members of the cluster may be analyzed to determine whether other members purchased a particular size of the item, and if so, the size purchased by the other members may serve as a basis to recommend a size that may best fit the consumer. For example, if other members of the cluster purchased a particular size, then that size may be recommended to the subject consumer, or if other members of the cluster purchased and then returned a particular size (e.g., for being too small), then another (e.g., larger) size may be recommended to the subject consumer.

    摘要翻译: 本发明的一些实施例提供了用于推荐主题项目的大小以适合受试者消费者的技术。 在一些实施例中,使用一种或多种数据聚类算法,基于许多消费者属性(例如,自我报告和/或推断的身高,体重,身体形状, 身体特征和/或购买历史(例如,购买产品套件的重叠度高的消费者))。 可以分析关于集群中其他消费者的信息,以得出关于主题项目的不同大小如何适合主题消费者的结论。 例如,可以分析集群的其他成员的购买历史以确定其他成员是否购买了该项目的特定大小,如果是,则由其他成员购买的尺寸可以作为推荐可能的尺寸的基础 最适合消费者。 例如,如果集群的其他成员购买了特定的大小,那么该尺寸可能被推荐给主题消费者,或者如果集群的其他成员购买了然后返回了特定尺寸(例如,太小),则另一个 (例如,更大)尺寸可能被推荐给主题消费者。

    Methods and apparatus for optimizing markdown pricing
    3.
    发明授权
    Methods and apparatus for optimizing markdown pricing 有权
    优化降价定价的方法和设备

    公开(公告)号:US07979299B1

    公开(公告)日:2011-07-12

    申请号:US11158264

    申请日:2005-06-21

    IPC分类号: G06Q99/00

    摘要: The invention provides methods and apparatus for optimizing markdown scheduling that group multiple retail sites into bins (or buckets) for purposes of scheduling markdown pricing on an item (or group of related items) sold by those sites. The groupings can be based, for example, on a metric that is a function of the current inventory of the item (or items) and its expected sales at each site. A markdown schedule is generated for the combined grouping of stores in each bucket, rather than for the individual stores that make up that bucket, thereby speeding price optimization determination. A report of those schedules can be used, for example, by pricing managers or other personnel to set prices at the sites. Alternatively, or in an addition, the schedules can be used in conjunction with an inventory control system to set prices for the items and/or on RFID or other electronic shelf displays.

    摘要翻译: 本发明提供了用于优化降级调度的方法和装置,其将多个零售点组合成箱(或桶),以便为由这些站点出售的物品(或相关物品组)调度降价定价。 分组可以基于例如与项目(或项目)的当前库存的函数及其在每个站点的预期销售量的度量。 为每个桶中的商店的组合分组而不是组成该桶的各个商店生成降价计划,从而加速价格优化确定。 可以使用这些时间表的报告,例如定价管理人员或其他人员在现场设定价格。 或者,或者另外,附表可以与库存控制系统一起使用以设置物品和/或RFID或其他电子货架显示器上的价格。

    Fit recommendation via collaborative inference
    4.
    发明授权
    Fit recommendation via collaborative inference 有权
    通过协作推理适合推荐

    公开(公告)号:US08478663B2

    公开(公告)日:2013-07-02

    申请号:US13192617

    申请日:2011-07-28

    IPC分类号: G06Q30/00

    CPC分类号: G06Q30/0631 G06Q30/00

    摘要: Some embodiments of the invention provide techniques for recommending a size of a subject item to fit a subject consumer. In some embodiments, clusters of consumers with fit characteristics similar to the subject consumer are identified, using one or more data clustering algorithms, based on any of numerous consumer attributes (e.g., self-reported and/or inferred height, weight, body shape, body characteristics, and/or purchase histories (e.g., consumers with high overlap in terms of sets of products purchased)). Information on other consumers in the cluster may be analyzed to draw conclusions on how different sizes of the subject item may fit the subject consumer. For example, the purchase history of other members of the cluster may be analyzed to determine whether other members purchased a particular size of the item, and if so, the size purchased by the other members may serve as a basis to recommend a size that may best fit the consumer. For example, if other members of the cluster purchased a particular size, then that size may be recommended to the subject consumer, or if other members of the cluster purchased and then returned a particular size (e.g., for being too small), then another (e.g., larger) size may be recommended to the subject consumer.

    摘要翻译: 本发明的一些实施例提供了用于推荐主题项目的大小以适合受试者消费者的技术。 在一些实施例中,使用一种或多种数据聚类算法,基于许多消费者属性(例如,自我报告和/或推断的身高,体重,身体形状, 身体特征和/或购买历史(例如,购买产品套件的重叠度高的消费者))。 可以分析关于集群中其他消费者的信息,以得出关于主题项目的不同大小如何适合主题消费者的结论。 例如,可以分析集群的其他成员的购买历史以确定其他成员是否购买了该项目的特定大小,如果是,则由其他成员购买的尺寸可以作为推荐可能的尺寸的基础 最适合消费者。 例如,如果集群的其他成员购买了特定的大小,那么该尺寸可能被推荐给主题消费者,或者如果集群的其他成员购买了然后返回了特定尺寸(例如,太小),则另一个 (例如,更大)尺寸可能被推荐给主题消费者。