公开(公告)号：US20140006171A1

公开(公告)日：2014-01-02

申请号：US13539266

申请日：2012-06-29

申请人： Patrick R. Jordan ,  Prabhakar Krishnamurthy ,  David Pardoe ,  Chris Leggetter ,  Sergei Vassilvitskii ,  Chris Bartels

发明人： Patrick R. Jordan ,  Prabhakar Krishnamurthy ,  David Pardoe ,  Chris Leggetter ,  Sergei Vassilvitskii ,  Chris Bartels

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0241 ,  G06Q30/0275 ,  G06Q30/08 ,  G06Q50/01

摘要： The present application relates to systems and computer-implemented methods for calculating a suggested market variable associated with an auction of an online advertisement realization opportunity. In some implementations, an optimization procedure may be operated, wherein the optimization procedure may comprise sending an initial market variable associated with one or more auctions to bidding agents; receiving from each of the bidding agents a response market variable associated with the initial market variable; determining according to an auction bidding rule a winning market variable from the response market variables; and substituting the initial market variable with the wining market variable. The optimization procedure may be operated repeatedly until the winning market variable stabilizes. Then the stabilized market variable may be sent to an advertiser as the suggested market variable.

摘要翻译： 本申请涉及用于计算与在线广告实现机会的拍卖相关联的建议的市场变量的系统和计算机实现的方法。 在一些实现中，可以操作优化过程，其中优化过程可以包括向投标代理发送与一个或多个拍卖相关联的初始市场变量; 从每个招标代理人接收与初始市场变量相关的应对市场变量; 根据拍卖竞价规则确定来自响应市场变量的获胜市场变量; 以市场变化为代价替代初始市场变量。 优化过程可以重复操作，直到获胜市场变量稳定。 然后，稳定的市场变量可以作为建议的市场变量发送给广告商。

公开(公告)号：US20140006141A1

公开(公告)日：2014-01-02

申请号：US13539271

申请日：2012-06-29

申请人： Sergei Vassilvitskii ,  Patrick R. Jordan ,  Chris Leggetter ,  Prabhakar Krishnamurthy ,  David Pardoe ,  Uri Nadav

发明人： Sergei Vassilvitskii ,  Patrick R. Jordan ,  Mohammad Mahdian ,  Chris Leggetter ,  Prabhakar Krishnamurthy ,  David Pardoe ,  Uri Nadav

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0241 ,  G06Q30/0275

摘要： The present application relates to systems and computer-implemented methods for determining a future bidding strategy regarding auctions associated with realization of an online advertisement. In some implementations, a server may be used to determine an optimized bid pacing parameter for an online advertisement based on a current bid pacing parameter associated with the online advertisement and an online advertisement supply information for a time period so that based on the optimized bid pacing, realization of the online advertisement over the time period substantially confirms to a spending strategy associated with the online advertisement during the time period. As such, the systems and computer-implemented methods may allow advertisers to control their spending strategy accurately during an advertising campaign.

摘要翻译： 本申请涉及用于确定关于在线广告的实现的拍卖的未来投标策略的系统和计算机实现的方法。 在一些实现中，可以使用服务器来基于与在线广告相关联的当前出价起搏参数和在一段时间段内的在线广告提供信息来确定用于在线广告的优化出价起搏参数，使得基于优化的出价起搏 在此期间实现在线广告基本上确认了在该时间段内与在线广告相关联的支出策略。 因此，系统和计算机实现的方法可以允许广告商在广告活动期间准确地控制他们的支出策略。

公开(公告)号：US20140006144A1

公开(公告)日：2014-01-02

申请号：US13539273

申请日：2012-06-29

申请人： David Pardoe ,  Patrick R. Jordan ,  Prabhakar Krishnamurthy ,  Sergei Vassilvitskii ,  Erik Vee

发明人： David Pardoe ,  Patrick R. Jordan ,  Prabhakar Krishnamurthy ,  Sergei Vassilvitskii ,  Erik Vee ,  Mohammad Mahdian ,  Mercin Mejran

IPC分类号： G06Q30/02

CPC分类号： G06Q30/02 ,  G06Q30/08

摘要： The present application relates to systems and computer-implemented methods for calculating a suggested reserve price associated with an opportunity to realize an online advertisement. In some implementations, data associated with historical online advertisement auctions are clustered based on a reference opportunity for realizing an online advertisement, wherein each historical online advertisement auction of the cluster is associated with a first bid price of higher value and a second bid price of lower value; a dominance relationship between a distribution of the first bid prices of the cluster and a distribution of the second bid prices of the cluster is determined; a reserve price associated with the cluster based on the dominance relationship is calculated; and the reserve price is stored as a suggested reserve price to realize an online advertisement, wherein the suggested reserve price is associated with the reference opportunity that is associated with the cluster.

摘要翻译： 本申请涉及用于计算与实现在线广告的机会相关联的建议的预留价格的系统和计算机实现的方法。 在一些实现中，与历史在线广告拍卖相关联的数据基于用于实现在线广告的参考机会而聚集，其中集群的每个历史在线广告拍卖与较高价格的第一投标价格和较低价格的第二投标价格相关联 值; 确定集群的第一投标价格分布与集群的第二投标价格分布之间的优势关系; 计算基于优势关系的与集群相关的储备价格; 储备价格作为建议的预留价格进行存储以实现在线广告，其中建议的储备价格与与集群相关联的参考机会相关联。

公开(公告)号：US20130166395A1

公开(公告)日：2013-06-27

申请号：US13333241

申请日：2011-12-21

申请人： Sergei Vassilvitskii ,  Chandrashekhar Nagarajan ,  Peiji Chen ,  Jian Yang ,  John Tomlin ,  Vijay Bharadwaj ,  Erik Vee ,  WenJing Ma

发明人： Sergei Vassilvitskii ,  Chandrashekhar Nagarajan ,  Peiji Chen ,  Jian Yang ,  John Tomlin ,  Vijay Bharadwaj ,  Erik Vee ,  WenJing Ma

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0244

摘要： The present application provides systems and corresponding methods for creating a delivery allocation plan in a network-based environment. The methods may include receiving and storing advertising contracts and data related to the advertising contracts; constructing a bipartite graph based on the received contract data; annotating each demand node; and receiving impression data and other eligible contract data. Thereafter, the method may include for each impression, calculating a first supply value and for each contract, calculating a first demand value. The first demand value may be used to calculate a second supply value and a delivery allocation may be calculated using the second supply value and the second demand value for each contract.

摘要翻译： 本申请提供在基于网络的环境中创建传送分配计划的系统和相应方法。 方法可以包括接收和存储与广告合同相关的广告合同和数据; 基于收到的合同数据构建二分图; 注释每个需求节点; 并接收展示数据和其他合格的合同数据。 此后，该方法可以包括对于每个印象，计算第一供应值，并且对于每个合约，可以计算第一需求值。 可以使用第一需求值来计算第二供应值，并且可以使用第二供应值和每个合同的第二需求值来计算交货分配。

公开(公告)号：US20110179019A1

公开(公告)日：2011-07-21

申请号：US12688364

申请日：2010-01-15

申请人： Sihem Amer-Yahia ,  Sergei Vassilvitskii ,  Cong Yu

发明人： Sihem Amer-Yahia ,  Sergei Vassilvitskii ,  Cong Yu

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： An improved method for information retrieval in web query and recommendation systems, where items that are likely unfamiliar to the users of the system, but potentially relevant, are recommended. In a recommendation system having ratings by a plurality of users for a plurality of items, items are assigned to one or more data regions based on item attributes or user activity. Source regions are identified for each of the data regions. For a given user, data regions with which both the user and the user's social network are unfamiliar are identified. Within a given data region, the relevance of items to the user within such regions is evaluated using ratings provided by other users who have entered ratings similar to the user in source regions for the data region. Items receiving the highest relevance score are recommended to the user.

摘要翻译： 一种改进的Web查询和推荐系统中的信息检索方法，推荐系统用户可能不熟悉的项目。 在具有用于多个项目的多个用户的评级的推荐系统中，基于项目属性或用户活动将项目分配给一个或多个数据区域。 为每个数据区域识别源区域。 对于给定的用户，识别用户和用户的社交网络不熟悉的数据区域。 在给定的数据区域内，使用在数据区域的源区域中输入与用户类似的评级的其他用户提供的评级来评估项目对这些区域内的用户的相关性。 建议用户接收到最高相关性分数的项目。

公开(公告)号：US20100250332A1

公开(公告)日：2010-09-30

申请号：US12414166

申请日：2009-03-30

申请人： Arpita Ghosh ,  Benjamin I.P. Rubinstein ,  Sergei Vassilvitskii ,  Martin Zinkevich

发明人： Arpita Ghosh ,  Benjamin I.P. Rubinstein ,  Sergei Vassilvitskii ,  Martin Zinkevich

IPC分类号： G06Q30/00 ,  G06N5/02

CPC分类号： G06Q30/08 ,  G06Q30/02 ,  G06Q30/0242 ,  G06Q30/0249 ,  G06Q30/0275 ,  G06Q30/0601

摘要： A system for performing adaptive bidding to secure Internet advertising impressions in an auction. Included are systems for analyzing advertising campaign objectives, including a campaign period, a target number of impressions, a target budget. An exemplary technique defines a bidding agent for performing the adaptive bidding seeking the minimum target spending of the budget. Objective results of the campaign such as average cost per won impression, total campaign duration relative to desired campaign period, and total expenditure relative to campaign budget can be optimized based on an empirically determined forecast. Techniques for adapting bids include statistically modeling winning bids during an exploration bidding phase, performing iterations for adjustment of the bid amounts using learn-while-bid adaptive bidding, learn-then-bid adaptive bidding, and guess-double-adjust adaptive bidding. Bidding tactics, especially those used to identify a minimum target bid and a maximum target bid used in bidding on an exchange are employed, and the results analyzed using statistical models.

摘要翻译： 用于执行自适应出价以在竞价中保护互联网广告印象的系统。 包括用于分析广告活动目标的系统，包括广告系列期间，目标数量的展示次数，目标预算。 一个示例性技术定义了一个投标代理，用于执行适应性投标，寻求预算的最低目标支出。 根据经验确定的预测，可以优化运动的客观结果，例如平均每赢得印象的成本，相对于期望的活动期间的总活动持续时间以及相对于活动预算的总支出。 适应投标的技术包括在勘探招标阶段统计建模中标，通过学习 - 竞标自适应竞标，学习竞标自适应竞标，猜测双重调整自适应竞价，进行迭代调整投标金额。 采用招标策略，特别是用于确定最低目标出价的标书和用于交易所投标的最高目标出价，并采用统计模型分析结果。

公开(公告)号：US20110270676A1

公开(公告)日：2011-11-03

申请号：US12771196

申请日：2010-04-30

申请人： Sergei Vassilvitskii ,  Jayavel Shanmugasundaram ,  Sumanth Jagannath ,  Erik Vee ,  Martin Zinkevich

发明人： Sergei Vassilvitskii ,  Jayavel Shanmugasundaram ,  Sumanth Jagannath ,  Erik Vee ,  Martin Zinkevich

IPC分类号： G06Q30/00 ,  G06N5/02

CPC分类号： G06Q30/02 ,  G06Q30/0251

摘要： A computer-implemented method and display advertising server network for serving impression opportunities to a frequency-capped guaranteed delivery contract in a system for delivery of display advertising to a user. The method includes steps for receiving, from a computer, an event predicate and a user ID corresponding to the user, retrieving, from an index engine, a set of eligible frequency-capped contracts, wherein an eligible contract comprises at least one target predicate matching at least a portion of the event predicate, and probabilistically selecting for serving, in a computer, the booked contract having a frequency cap specification, only when the selected frequency-capped contract can be served to the user without violating the frequency cap specification. Exemplary embodiments include generating a pseudo-random number sequence, and then selecting a particular pseudo-random number from the series of pseudo-random numbers, the selected particular pseudo-random number being based on the user ID, a visit count, a URL.

摘要翻译： 一种计算机实现的方法和显示广告服务器网络，用于向系统中的用于向用户传送显示广告的频率上限的保证递送合同提供展示机会。 该方法包括从计算机接收与用户相对应的事件谓词和用户ID的步骤，从索引引擎检索一组合格的频率上限合同，其中符合条件的合同包括至少一个目标谓词匹配 至少部分事件谓词，并且在计算机中概率地选择用于服务具有频率上限规范的预约合同，只有当所选择的频率上限的合同可以在不违反频率上限规范的情况下被提供给用户时。 示例性实施例包括生成伪随机数序列，然后从所述一系列伪随机数中选择特定的伪随机数，所选择的特定伪随机数基于用户ID，访问次数，URL。

公开(公告)号：US20100125506A1

公开(公告)日：2010-05-20

申请号：US12274464

申请日：2008-11-20

申请人： Sergei Vassilvitskii ,  Colin Brady ,  Rica Gonen

发明人： Sergei Vassilvitskii ,  Colin Brady ,  Rica Gonen

IPC分类号： G06Q30/00

CPC分类号： G06Q30/08 ,  G06Q30/02 ,  G06Q30/0273 ,  G06Q30/0601

摘要： Search engines and sponsored search auctions are provided that enable the use of different reserve prices corresponding to different advertisement slots on a search results page. In one implementation, a search engine includes a query processor and a sponsored search auction. The query processor is configured to receive a query from an electronic device associated with a user, to determine a plurality of reserve prices corresponding to a plurality of advertisement slots of a search results page, and to determine a plurality of bid prices for the advertisement slots of the search results page corresponding to a plurality of bidders. The sponsored search auction is configured to allocate a bidder or a null (e.g., no advertisement) to each advertisement slot of the search results page, taking into account the plurality of reserve prices associated with the advertisement slots of the search results page.

摘要翻译： 提供搜索引擎和赞助商搜索拍卖，可以在搜索结果页面上使用与不同广告位相对应的不同预留价格。 在一个实现中，搜索引擎包括查询处理器和赞助的搜索拍卖。 查询处理器被配置为从与用户相关联的电子设备接收查询，以确定对应于搜索结果页面的多个广告时隙的多个预留价格，并且确定广告时隙的多个投标价格 对应于多个投标者的搜索结果页面。 赞助搜索拍卖被配置为考虑到与搜索结果页面的广告时隙相关联的多个预留价格，将搜索者或搜索结果页面的每个广告时段的空值（例如，无广告）分配。

公开(公告)号：US20130268374A1

公开(公告)日：2013-10-10

申请号：US13441672

申请日：2012-04-06

申请人： Kishore Papineni ,  Preston McAfee ,  John Langford ,  Sergei Vassilvitskii

发明人： Kishore Papineni ,  Preston McAfee ,  John Langford ,  Sergei Vassilvitskii

IPC分类号： G06Q30/02

CPC分类号： G06Q30/02

摘要： Techniques are provided for use in an auction in which selected content items, or advertisements, of content providers, or advertisers, are selected and served, and in which, for an item served in response to a serving opportunity, contingent upon occurrence of a specified user action, an associated provider's account is charged a first sum and an associated publisher's account is credited a second sum. Performance of particular content items may be explored, such as ones for which little or no historical performance information may be available. Content item selection may be based at least in part on an objective of acquiring learning information that can be used in prediction of future performance of the content item. The associated provider's account may be charged a sum that reflects a learning value component, but the associated publisher's account may be credited a sum that does not reflect a learning value component.

摘要翻译： 技术被提供用于拍卖中，其中内容提供商或广告商的所选择的内容项目或广告被选择和服务，并且其中针对响应于服务机会而服务的项目，取决于发生指定的 用户操作，相关联的提供商的帐户将收取第一笔款项，相关联的发布商的帐户将被记入第二笔款项。 可以探索特定内容项目的性能，例如可能没有或没有历史性能信息可用的性能。 内容项目选择可以至少部分地基于获取可用于预测内容项目的未来表现的学习信息的目标。 相关提供商的帐户可能会收取一笔反映学习价值组成部分的金额，但相关发布商的帐户可能会记入不反映学习价值组成部分的金额。

公开(公告)号：US08204878B2

公开(公告)日：2012-06-19

申请号：US12688364

申请日：2010-01-15

申请人： Sihem Amer-Yahia ,  Sergei Vassilvitskii ,  Cong Yu

发明人： Sihem Amer-Yahia ,  Sergei Vassilvitskii ,  Cong Yu

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： An improved method for information retrieval in web query and recommendation systems, where items that are likely unfamiliar to the users of the system, but potentially relevant, are recommended. In a recommendation system having ratings by a plurality of users for a plurality of items, items are assigned to one or more data regions based on item attributes or user activity. Source regions are identified for each of the data regions. For a given user, data regions with which both the user and the user's social network are unfamiliar are identified. Within a given data region, the relevance of items to the user within such regions is evaluated using ratings provided by other users who have entered ratings similar to the user in source regions for the data region. Items receiving the highest relevance score are recommended to the user.

摘要翻译： 一种改进的Web查询和推荐系统中的信息检索方法，推荐系统用户可能不熟悉的项目。 在具有用于多个项目的多个用户的评级的推荐系统中，基于项目属性或用户活动将项目分配给一个或多个数据区域。 为每个数据区域识别源区域。 对于给定的用户，识别用户和用户的社交网络不熟悉的数据区域。 在给定的数据区域内，使用在数据区域的源区域中输入与用户类似的评级的其他用户提供的评级来评估项目对这些区域内的用户的相关性。 建议用户接收到最高相关性分数的项目。