公开(公告)号：US20090132340A1

公开(公告)日：2009-05-21

申请号：US11944089

申请日：2007-11-21

申请人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

发明人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

IPC分类号： G06Q30/00 ,  G06F17/10

CPC分类号： G06Q30/02 ,  G06Q30/0201 ,  G06Q30/0246

摘要： A method for maximizing page yield in advertisement display to Web users includes tracking click activity associated with advertisements displayed to users through a hierarchal set of search results pages associated with a keyword; tracking bidding activity by advertisers related to the keyword and corresponding advertisements of the advertisements; applying at least one component model to the click or bidding activity as correlated with a particular search results page of the hierarchal set of search results pages via which the advertisements receiving the click activity are displayed, wherein the at least one component model generates a set of output values representative of the tracked click activity; and providing the output values to the at least one component model to iteratively optimize a number of advertisements displayed on the particular search results page via which at least some of the advertisements are displayed in response to a query for the keyword.

摘要翻译： 用于使广告显示中的页面收益最大化到Web用户的方法包括通过与关键字相关联的搜索结果页面的分层集合跟踪与向用户显示的广告相关联的点击活动; 与关键字相关的广告客户追踪出价活动，广告对应的广告; 将至少一个组件模型应用于与显示接收点击活动的广告的层级组搜索结果页面的特定搜索结果页面相关联的点击或投标活动，其中所述至少一个组件模型生成一组 代表跟踪的点击活动的输出值; 以及将所述输出值提供给所述至少一个组件模型，以迭代地优化在所述特定搜索结果页面上显示的广告数量，通过所述多个广告响应于所述关键字的查询显示所述广告中的至少一些。

公开(公告)号：US20120290406A1

公开(公告)日：2012-11-15

申请号：US13561179

申请日：2012-07-30

申请人： Kerem Tomak

发明人： Kerem Tomak

IPC分类号： G06Q30/02

CPC分类号： G06Q30/08 ,  G06Q30/0601

摘要： Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

摘要翻译： 用于导出学习算法的最优参数的设备，方法和系统，以最大限度地提高出价词汇的在线关键词拍卖的目标函数。 本发明的一些实施例基于出价条款的历史数据模拟在线关键词拍卖，其中模拟拍卖的参数（例如出价的市场准备价格的参数）由自适应学习算法确定。 通过随机优化方法优化学习算法的参数值，以最大限度地提高出价项的拍卖的目标函数。

公开(公告)号：US20080091524A1

公开(公告)日：2008-04-17

申请号：US11580586

申请日：2006-10-13

申请人： Tak W. Yan ,  Kerem Tomak ,  Chi-Chao Chang

发明人： Tak W. Yan ,  Kerem Tomak ,  Chi-Chao Chang

IPC分类号： G06Q30/00

CPC分类号： G06Q30/02 ,  G06Q30/0246 ,  G06Q30/0247 ,  G06Q30/0257 ,  G06Q30/0277

摘要： The present invention relates to systems and methods for generating an adjustment factor for a cost associated with a user selection of an advertisement displayed at a website. The method of the present invention comprises retrieving analytics data and traffic quality metric data associated with the website, and calculating a traffic quality score for the website. An adjustment factor for the website is calculated based upon the traffic quality score associated with the website and a benchmark traffic quality score.

摘要翻译： 本发明涉及用于生成与在网站上显示的广告的用户选择相关联的成本的调整因子的系统和方法。 本发明的方法包括检索与网站相关联的分析数据和流量质量量度数据，以及计算网站的流量质量得分。 根据与网站相关的流量质量得分和基准流量质量得分，计算网站的调整系数。

公开(公告)号：US20140040013A1

公开(公告)日：2014-02-06

申请号：US13563332

申请日：2012-07-31

申请人： Albert ZHAI ,  Ruxi ZHANG ,  Kerem TOMAK

发明人： Albert ZHAI ,  Ruxi ZHANG ,  Kerem TOMAK

IPC分类号： G06Q30/02

CPC分类号： G06Q30/0242 ,  G06Q30/0246 ,  G06Q30/06

摘要： A method including the steps of generating, using one or more processors, a first statistical model fitted to first data related to in-store purchases resulting from economic browses made by known visitors to an online website, generating, using one or more processors, a bias correction to the first statistical model based on comparison between observed behavior of all unknown visitors to the online website and observed behavior of all known visitors to the online website, applying, using one or more processors, the generated bias correction to the first statistical model so as to obtain a second statistical model fitted to second data related to in-store purchases resulting from economic browses made by unknown visitors to the online website, and calculating, using one or more processors, a total monetary amount resulting from the in-store purchases made by the known and unknown visitors based on the first and second data.

摘要翻译： 一种方法，包括以下步骤：使用一个或多个处理器，将第一统计模型拟合到与由在线网站上的已知访问者进行的经济浏览相结合的店内购买相关的第一数据，使用一个或多个处理器生成 基于观察到在线网站的所有未知访问者的观察行为与观察到在线网站的所有已知访问者的行为之间的比较来对第一统计模型进行偏差校正，将使用一个或多个处理器的生成的偏差校正应用于第一统计模型 以获得第二统计模型，其适合于由在线网站的未知访问者进行的经济浏览导致的与店内购买相关的第二数据，以及使用一个或多个处理器计算从店内获得的总金额 根据第一和第二个数据，由已知和未知的访问者进行购买。

公开(公告)号：US08069083B2

公开(公告)日：2011-11-29

申请号：US11835733

申请日：2007-08-08

申请人： Mohammad Mahdian ,  Kerem Tomak

发明人： Mohammad Mahdian ,  Kerem Tomak

IPC分类号： G06Q30/00

CPC分类号： G06Q30/02 ,  G06Q30/0239 ,  G06Q30/0242 ,  G06Q30/0247 ,  G06Q30/0257 ,  G06Q30/0273 ,  G06Q30/0274 ,  G06Q30/0275 ,  G06Q40/04

摘要： A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

摘要翻译： 公开了一种用于每次付费付费（PPA）广告模式的系统。 广告客户会针对已报告的每个操作报告操作并为广告提供商付费。 付款可以根据报告的行动速度。 可以基于每个报告的动作来更新动作率，其可以修改该动作的支付，并且可以修改先前动作的支付。 可能会向广告客户收取一次性溢价，并且可以建立最低行动费率，以鼓励广告客户准确地报告行动。

公开(公告)号：US07805331B2

公开(公告)日：2010-09-28

申请号：US11943192

申请日：2007-11-20

申请人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

发明人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

IPC分类号： G06F17/00

CPC分类号： G06Q30/02 ,  G06Q30/0201 ,  G06Q30/0241

摘要： A method for valuating an advertiser considered for acquisition includes capturing click-related data by users with reference to a plurality of advertisements owned by a plurality of advertisers in a keyword market; calculating a marginal value of each of the plurality of advertisers as a function of a plurality of averaged market factors, wherein the marginal value of an additional advertiser is also calculated to result in at least an estimated displaced revenue if at least one advertisement of the additional advertiser for at least one keyword were competitively included in the keyword market; and deciding whether to pursue the additional advertiser based on the marginal value of the additional advertiser as associated with the at least one keyword.

摘要翻译： 用于评估被考虑用于获取的广告商的方法包括：参考由关键词市场中的多个广告商拥有的多个广告来捕获用户的点击相关数据; 根据多个平均市场因素来计算多个广告商中的每一个的边际价值，其中如果附加的至少一个广告的至少一个广告还附加了另外的广告商的边际价值，还计算出至少一个估计的流离失所的收入 至少有一个关键字的广告客户竞争地包含在关键字市场中; 以及基于与所述至少一个关键字相关联的所述附加广告商的边际值来决定是否追求所述另外的广告商。

公开(公告)号：US20090132336A1

公开(公告)日：2009-05-21

申请号：US11943192

申请日：2007-11-20

申请人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

发明人： Ramazan Demir ,  Jiaqi Jin ,  Kerem Tomak ,  Supratim Roy Chaudhury

IPC分类号： G06Q10/00 ,  G06F17/10

CPC分类号： G06Q30/02 ,  G06Q30/0201 ,  G06Q30/0241

摘要： A method for valuating an advertiser considered for acquisition includes capturing click-related data by users with reference to a plurality of advertisements owned by a plurality of advertisers in a keyword market; calculating a marginal value of each of the plurality of advertisers as a function of a plurality of averaged market factors, wherein the marginal value of an additional advertiser is also calculated to result in at least an estimated displaced revenue if at least one advertisement of the additional advertiser for at least one keyword were competitively included in the keyword market; and deciding whether to pursue the additional advertiser based on the marginal value of the additional advertiser as associated with the at least one keyword.

摘要翻译： 用于评估被考虑用于获取的广告商的方法包括：参考由关键词市场中的多个广告商拥有的多个广告来捕获用户的点击相关数据; 根据多个平均市场因素来计算多个广告商中的每一个的边际价值，其中如果附加的至少一个广告的至少一个广告还附加了另外的广告商的边际价值，还计算出至少一个估计的流离失所的收入 至少有一个关键字的广告客户竞争地包含在关键字市场中; 以及基于与所述至少一个关键字相关联的所述附加广告商的边际值来决定是否追求所述另外的广告商。

公开(公告)号：US20090043648A1

公开(公告)日：2009-02-12

申请号：US11835733

申请日：2007-08-08

申请人： Mohammad Mahdian ,  Kerem Tomak

发明人： Mohammad Mahdian ,  Kerem Tomak

IPC分类号： G06Q30/00

CPC分类号： G06Q30/02 ,  G06Q30/0239 ,  G06Q30/0242 ,  G06Q30/0247 ,  G06Q30/0257 ,  G06Q30/0273 ,  G06Q30/0274 ,  G06Q30/0275 ,  G06Q40/04

摘要： A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

摘要翻译： 公开了一种用于每次付费付费（PPA）广告模式的系统。 广告客户会针对已报告的每个操作报告操作并为广告提供商付费。 付款可以根据报告的行动速度。 可以基于每个报告的动作来更新动作率，其可以修改该动作的支付，并且可以修改先前动作的支付。 可能会向广告客户收取一次性溢价，并且可以建立最低行动费率，以鼓励广告客户准确地报告行动。

公开(公告)号：US08484094B2

公开(公告)日：2013-07-09

申请号：US13561179

申请日：2012-07-30

申请人： Kerem Tomak

发明人： Kerem Tomak

IPC分类号： G06Q40/00

CPC分类号： G06Q30/08 ,  G06Q30/0601

摘要： Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

摘要翻译： 用于导出学习算法的最优参数的设备，方法和系统，以最大限度地提高出价词汇的在线关键词拍卖的目标函数。 本发明的一些实施例基于出价条款的历史数据模拟在线关键词拍卖，其中模拟拍卖的参数（例如出价的市场准备价格的参数）由自适应学习算法确定。 通过随机优化方法优化学习算法的参数值，以最大限度地提高出价项的拍卖的目标函数。

公开(公告)号：US08260680B2

公开(公告)日：2012-09-04

申请号：US12338460

申请日：2008-12-18

申请人： Kerem Tomak

发明人： Kerem Tomak

IPC分类号： G06Q40/00

CPC分类号： G06Q30/08 ,  G06Q30/0601

摘要： Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.

摘要翻译： 用于导出学习算法的最优参数的设备，方法和系统，以最大限度地提高出价词汇的在线关键词拍卖的目标函数。 本发明的一些实施例基于出价条款的历史数据模拟在线关键词拍卖，其中模拟拍卖的参数（例如出价的市场准备价格的参数）由自适应学习算法确定。 通过随机优化方法优化学习算法的参数值，以最大限度地提高出价项的拍卖的目标函数。