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    • 102. 发明申请
    • ADVERTISEMENT SPACE ALLOCATION
    • 广告空间分配
    • US20090210287A1
    • 2009-08-20
    • US12032695
    • 2008-02-18
    • David M. ChickeringYagil EngelGuy DassaJody BiggsChristopher A. Meek
    • David M. ChickeringYagil EngelGuy DassaJody BiggsChristopher A. Meek
    • G06Q30/00G06Q10/00
    • G06Q30/02G06Q30/0267G06Q30/0275
    • A user utility function is implemented in allocating advertisement space to one or more potential advertisers. The user utility function allows advertisement space to be allocated based upon, among other things, the expected utility or usefulness that a proposed advertisement will have to a user. The user utility function, for example, compares proposed advertisements to historical user actions to generate respective user utility values for advertisements (e.g., based upon user responses to advertisements for particular types of product, responses to advertisements from particular types of sellers, etc.). The user utility values can then be applied to bids submitted by advertisers for advertisement space for particular advertisements to obtain modified bids. The modified bids thus reflect, among other things, the expected utility of an advertisement to a user, and thus allow an advertisement host to allocate advertisement space accordingly.
    • 在向一个或多个潜在广告商分配广告空间中实现用户效用函数。 用户效用函数允许基于所提议的广告将对用户具有的预期效用或有用性来分配广告空间。 例如,用户效用函数将所提出的广告与历史用户动作进行比较,以生成广告的相应用户效用值(例如,基于用户对特定类型的产品的广告的响应,对来自特定类型的卖家的广告的响应等) 。 然后,可以将用户效用值应用于广告商提交的用于特定广告的广告空间的出价以获得修改的出价。 因此,修改的出价因此反映了广告对用户的期望效用,并且因此允许广告主主机相应地分配广告空间。
    • 110. 发明授权
    • Distributed reservoir sampling for web applications
    • Web应用程序的分布式油藏采样
    • US07308447B2
    • 2007-12-11
    • US11212301
    • 2005-08-26
    • David M. ChickeringAshis K. RoyChristopher A. Meek
    • David M. ChickeringAshis K. RoyChristopher A. Meek
    • G06F17/30
    • G06F17/30861Y10S707/99936
    • Random samples without replacement are extracted from a distributed set of items by leveraging techniques for aggregating sampled subsets of the distributed set. This provides a uniform random sample without replacement representative of the distributed set, allowing statistical information to be gleaned from extremely large sets of distributed information. Subset random samples without replacement are extracted from independent subsets of the distributed set of items. The subset random samples are then aggregated to provide a uniform random sample without replacement of a fixed size that is representative of a distributed set of items of unknown size. In one instance, a multivariate hyper-geometric distribution is sampled by breaking up the multivariate hyper-geometric distribution into a set of univariate hyper-geometric distributions. Individual items of a uniform random sample without replacement are then determined utilizing a normal approximation of the univariate hyper-geometric distributions and a finite population correction factor.
    • 通过利用用于聚合分布集合的采样子集的技术,从分布式集合中提取不带替换的随机样本。 这提供了一个统一的随机样本,而不需要替代代表分布集,允许从极大的分布式信息集中收集统计信息。 从分配的项目集的独立子集中提取不具有替换的子集随机样本。 然后将子集随机样本聚合以提供均匀的随机样本,而不替换代表未知大小的分布式项目集合的固定大小。 在一种情况下,通过将多变量超几何分布分解成一组单变量超几何分布来对多变量超几何分布进行采样。 然后使用单变量超几何分布的正态近似和有限群体校正因子来确定不具有替换的均匀随机样本的单个项目。