公开(公告)号：US20170078415A1

公开(公告)日：2017-03-16

申请号：US14854726

申请日：2015-09-15

Applicant: Yahoo! Inc.

Inventor： Liang Wang ,  Zhen Xia ,  Datong Chen ,  Musen Wen

IPC: H04L29/08

Abstract: Systems and methods for identifying users according to their activity are disclosed. The identification of a user includes accessing a user activity log having a plurality of identifiers and corresponding activity information for each identifier, determining identifiers having correlating activity information, and assigning identifiers having correlating activity information to a common user.

Abstract translation: 公开了根据其活动来识别用户的系统和方法。 用户的识别包括访问具有多个标识符的用户活动日志和每个标识符的相应活动信息，确定具有相关活动信息的标识符，以及将具有相关活动信息的标识符分配给公共用户。

公开(公告)号：US20140081696A1

公开(公告)日：2014-03-20

申请号：US14089186

申请日：2013-11-25

Applicant: Yahoo! Inc.

Inventor： Konstantin Salomatin ,  Datong Chen ,  Qi He ,  Peiji Chen

IPC: G06Q10/10 ,  G06Q30/02 ,  G06Q10/06

CPC classification number: G06Q10/1095 ,  G06Q10/06 ,  G06Q30/0202 ,  G06Q30/0241

Abstract: Systems and methods for automatically forecasting the future availability of one or more resources, such as Internet advertising opportunities, are described herein. In accordance with various embodiments, a forecasting model that accounts for event-driven resource availability is trained based both on historical supply data and calendar information specifying events and event duration. The trained forecasting model is then used to forecast the availability of resources at one or more specified future time periods. In accordance with certain embodiments, the forecasting model comprises a Gaussian process model that has an event-driven kernel as a covariance function.

Abstract translation: 这里描述了用于自动预测一个或多个资源（例如因特网广告机会）的将来可用性的系统和方法。 根据各种实施例，基于历史供应数据和指定事件和事件持续时间的日历信息来训练考虑事件驱动的资源可用性的预测模型。 然后使用经过训练的预测模型来预测在一个或多个指定的未来时间段的资源的可用性。 根据某些实施例，预测模型包括具有作为协方差函数的事件驱动内核的高斯过程模型。

公开(公告)号：US20140019232A1

公开(公告)日：2014-01-16

申请号：US14031943

申请日：2013-09-19

Applicant: Yahoo! Inc.

Inventor： Erik Vee ,  Jayavel Shanmugasundaram ,  Long Ji Lin ,  Peiji Chen ,  Datong Chen ,  Qi He

IPC: G06Q30/02

CPC classification number: G06Q30/0246 ,  G06Q30/00

Abstract: Techniques are described herein for using an impression-trend technique to provide a display advertising supply forecast. A display advertising supply forecast is an estimate of a number of impressions, which are to occur in a future time period, that have specified attribute values. For example, the specified attribute values may be descriptive of impressions with respect to which an advertiser wishes to place ads. An impression-trend technique is a forecasting technique that uses trends regarding past impressions to forecast a number of future impressions that have specified attribute values. The past impressions include attribute values that are related to the specified attribute values.

Abstract translation: 本文描述了使用印象趋势技术来提供展示广告供应预测的技术。 展示广告供应预测是对未来时间段内具有指定属性值的展示次数的估计。 例如，指定的属性值可以描述广告客户希望放置广告的展示次数。 印象趋势技术是一种预测技术，其使用关于过去展示的趋势来预测指定属性值的未来展示次数。 过去的展示包括与指定的属性值相关的属性值。