公开(公告)号：US20140249914A1

公开(公告)日：2014-09-04

申请号：US14201514

申请日：2014-03-07

Applicant: Yahoo! Inc.

Inventor： Pavel Berkhin ,  Usama M. Fayyad ,  Scott Gaffney ,  Bassel Ojjeh ,  Rajesh Girish Parekh ,  Andrew Tomkins

IPC: G06Q30/02

CPC classification number: G06Q30/0244 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0249 ,  G06Q30/0275

Abstract: Methods and apparatus are described for optimally allocating an online advertising budget for a search engine marketing (SEM) campaign among a fixed set of keywords.

Abstract translation: 描述了用于在一组固定的关键字之中为搜索引擎营销（SEM）活动最佳地分配在线广告预算的方法和装置。

公开(公告)号：US08655724B2

公开(公告)日：2014-02-18

申请号：US14018873

申请日：2013-09-05

Applicant: Yahoo! Inc.

Inventor： Richard Tao-Hwa Chow ,  Pavel Berkhin ,  Elena Eneva ,  Boris Klots ,  Nicolas Eddy Mayoraz ,  Rajesh Girish Parekh

IPC: G06Q30/00

CPC classification number: G06Q30/0248 ,  G06Q10/0635 ,  G06Q30/0185 ,  G06Q30/02

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract translation: 描述了用于评估用于将多个事件中的每一个分类为第一事件类型或第二事件类型的二进制分类系统的方法和装置。 参考验证数据，可以独立地验证第一事件类型的至少一些事件。 二进制分类系统易于将第一事件类型的事件分类为第二事件类型的第一错误类型和将第二事件类型的事件分类为第一事件类型的第二错误类型。 参照目标函数对二进制分类系统的第一配置的操作进行评估。 目标函数是通过参照验证数据表示第一错误类型的错误数量的第二错误类型的错误数，并且假设多个中的第一和第二事件类型的相对比例 的事件。

公开(公告)号：US20170140424A9

公开(公告)日：2017-05-18

申请号：US13739400

申请日：2013-01-11

Applicant: YAHOO! INC.

Inventor： John Canny ,  Shi Zhong ,  Scott Gaffney ,  Chad Brower ,  Pavel Berkhin ,  George H. John

IPC: G06Q30/02

CPC classification number: G06Q30/0251 ,  G06F17/00 ,  G06N5/02

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

公开(公告)号：US20140006145A1

公开(公告)日：2014-01-02

申请号：US14018873

申请日：2013-09-05

Applicant: Yahoo! Inc.

Inventor： Richard Tao-Hwa Chow ,  Pavel Berkhin ,  Elena Eneva ,  Boris Klots ,  Nicolas Eddy Mayoraz ,  Rajesh Girish Parekh

IPC: G06Q30/02

CPC classification number: G06Q30/0248 ,  G06Q10/0635 ,  G06Q30/0185 ,  G06Q30/02

Abstract: Methods and apparatus are described for evaluating a binary classification system operable to classify each of a plurality of events as a first event type or a second event type. At least some of the events of the first event type are independently verifiable with reference to verification data. The binary classification system is susceptible to a first error type in which events of the first event type are classified as the second event type, and a second error type in which events of the second event type are classified as the first event type. Operation of a first configuration of the binary classification system is evaluated with reference to an objective function. The objective function is derived by expressing a number of errors of the second error type in terms of a number of errors of the first error type with reference to the verification data, and by assuming relative proportions of the first and second event types within the plurality of events.

Abstract translation: 描述了用于评估用于将多个事件中的每一个分类为第一事件类型或第二事件类型的二进制分类系统的方法和装置。 参考验证数据，可以独立地验证第一事件类型的至少一些事件。 二进制分类系统易于将第一事件类型的事件分类为第二事件类型的第一错误类型和将第二事件类型的事件分类为第一事件类型的第二错误类型。 参照目标函数对二进制分类系统的第一配置的操作进行评估。 目标函数是通过参照验证数据表示第一错误类型的错误数量的第二错误类型的错误数，并且假设多个中的第一和第二事件类型的相对比例 的事件。

公开(公告)号：US20140200999A1

公开(公告)日：2014-07-17

申请号：US13739400

申请日：2013-01-11

Applicant: YAHOO! INC.

Inventor： John Canny ,  Shi Zhong ,  Scott Gaffney ,  Chad Brower ,  Pavel Berkhin ,  George H. John

IPC: G06Q30/02

CPC classification number: G06Q30/0251 ,  G06F17/00 ,  G06N5/02

Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

Abstract translation: 定向的方法接收几个粒度事件并预处理所接收的粒状事件，从而生成预处理的数据，以便于基于粒状事件构建模型。 该方法通过使用预处理数据生成预测模型。 预测模型用于确定用户动作的可能性。 该方法训练预测模型。 用于定位的系统包括粒状事件，用于接收粒度事件的预处理器，模型生成器和模型。 预处理器具有一个或多个用于修剪，聚合，聚类和/或过滤中的至少一个的模块。 模型生成器用于基于粒度事件构建模型，模型用于确定用户操作的可能性。 一些实施例的系统还包括若干用户，用于从几个用户中选择特定用户组的选择器，训练模型和评分模块。

公开(公告)号：US20130097184A1

公开(公告)日：2013-04-18

申请号：US13709764

申请日：2012-12-10

Applicant: Yahoo! Inc.

Inventor： Pavel Berkhin ,  Farzin Maghoul

IPC: G06F17/30

CPC classification number: G06F16/23 ,  G06F16/9535

Abstract: Trust networks in a recommender system are automatically updated in response to user feedback on recommendations provided by the trust network. In response to a user request, a set of referrals is generated, with some of the referrals being recommended based on judgment data received from members of the trust network. If the user evaluates the recommended referral, a trust parameter for at least one of the trust network members is updated based on the evaluation.

Abstract translation: 响应于用户对由信任网络提供的建议的反馈，推荐系统中的信任网络被自动更新。 响应于用户请求，生成一组引荐，基于从信任网络的成员接收的判断数据推荐一些推荐。 如果用户评估推荐的引用，则基于评估更新至少一个信任网络成员的信任参数。