公开(公告)号：US09858587B2

公开(公告)日：2018-01-02

申请号：US14103589

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Little ,  William Patrick Kee ,  Bozhena Bidyuk ,  Chao Cai ,  David Earl Barney ,  Stefan Schnabl

IPC: G06Q30/00 ,  G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating a data-driven attribution model are described. A processor identifies visits to a website. The processor identifies a path for each visitor identifier associated with the visits. The processor determines, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion. The processor calculates, for each of a plurality of the path types, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated. The processor determines, for each event, an attribution credit based on the calculated counterfactual gain of the event. The processor then stores the attribution credits of each of the events.

公开(公告)号：US09858588B2

公开(公告)日：2018-01-02

申请号：US14264666

申请日：2014-04-29

Applicant: Google Inc.

Inventor： Stefan Schnabl ,  John Chih Chang Huang ,  Hongxu Cai ,  William Patrick Kee ,  Bozhena Bidyuk ,  Chao Cai ,  Xiaosa Zhao ,  James Edward Stewart ,  Richard Edward Little ,  Todd Morris Jackson

IPC: G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Methods and systems for providing for display attribution data associated with one or more events are disclosed. Processor identifies channels from paths including events corresponding to position data identifying a position along the path at which the event was performed. Processor determines attribution credits assigned to each event included in the paths corresponding to the channel. Processor determines a number of attribution credits assigned to the channel. Processor identifies, from the paths, a plurality of event-position pairs. Each event-position pair corresponds to events that correspond to a respective channel and are performed at a respective position of the plurality of paths corresponding to the event-position pair. Processor determines, for each identified event-position pair, a weighting based on an aggregate of the attribution credits assigned to the events to which the event-position pair corresponds. Processor provides, for display, a visual object including an indicator to display the determined weightings.

公开(公告)号：US09858586B2

公开(公告)日：2018-01-02

申请号：US14103453

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Edward Little ,  Bozhena Bidyuk ,  Chao Cai ,  Todd Morris Jackson ,  John Chih Chang Huang

IPC: G06Q30/00 ,  G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating rules for assigning attribution credit across events, includes, identifying, by a processor, conversions at a website. The processor identifies path types associated with the conversions. Each path type identifies events and a index position indicating an event's relative position. The processor identifies a subset of the identified path types to be rewritten according to a path rewriting policy. The processor then rewrites the identified subset of the identified path types as rewritten path types. The processor determines, for each of the rewritten path types and remaining identified path types associated with the identified conversions, attribution credits for each event included in the path type. The processor creates, for each of the rewritten path types and remaining identified path types associated with the identified conversions, a rule for assigning the determined attribution credit to each event of the path type for which the rule is created.

公开(公告)号：US09462083B1

公开(公告)日：2016-10-04

申请号：US13833459

申请日：2013-03-15

Applicant: Google Inc.

Inventor： Yuan Zhuge ,  Xiuduan Fang ,  Niranjan Heddese Sitaram Shastry ,  Nagaraju Pothineni ,  Sagnik Nandy ,  Jesse Savage ,  Sissie Hsiao ,  Chao Cai

IPC: H04L29/06

CPC classification number: H04L67/42 ,  G06Q30/02 ,  H04L67/02 ,  H04L67/10 ,  H04L67/20

Abstract: The present disclosure is directed generally to systems and methods for the server side matching of web analytics and content viewing. According to the methods and systems disclosed herein, a first identifier is delivered to a client device when the client device accesses a first website. If the client device later accesses of a second website the first identifier can be processed by the system to determine if the client device previously accessed the first website.

Abstract translation: 本公开一般涉及用于网络分析和内容观看的服务器端匹配的系统和方法。 根据本文公开的方法和系统，当客户端设备访问第一网站时，第一标识符被传送到客户端设备。 如果客户端设备稍后访问第二个网站，系统可以处理第一个标识符，以确定客户端设备以前是否访问过第一个网站。

公开(公告)号：US09430519B1

公开(公告)日：2016-08-30

申请号：US13951770

申请日：2013-07-26

Applicant: Google Inc.

Inventor： Chao Cai ,  Eric W. Ewald ,  Cameron M. Tangney ,  Sagnik Nandy

IPC: G06F17/30

CPC classification number: G06F17/30386 ,  G06F17/30457 ,  G06F17/30489 ,  G06F17/3053

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dynamically generating and configuring pre-aggregated datasets optimized for responding to particular types of data requests made against a large sub-optimal multidimensional dataset are disclosed. A dynamic aggregator monitors the query types and response latencies associated with queries made against the large multidimensional dataset. The dynamic aggregator defines pre-aggregated datasets based on the types of queries received from users and calculates a respective benefit score for each pre-aggregated dataset. The benefit score of each pre-aggregated dataset can be based on the recorded latencies and query count for the pre-aggregated dataset. The dynamic aggregator can decide whether to generate and/or maintain particular pre-aggregated datasets based on the current values of the benefit scores associated with the particular pre-aggregated datasets.

公开(公告)号：US20150237395A1

公开(公告)日：2015-08-20

申请号：US14527481

申请日：2014-10-29

Applicant: Google Inc.

Inventor： David Barney ,  Chao Cai ,  Timothy Wright ,  William Patrick Kee

IPC: H04N21/442 ,  H04N21/258

CPC classification number: H04N21/44213 ,  H04H60/31 ,  H04H60/45 ,  H04H60/66 ,  H04N21/25883

Abstract: The present disclosure provides systems and methods for enhancing audience measurement data. Offline and online audience measurement data may be compared and correlated to improve the quality of each data and source set. Positive correlations between the offline and online data sets related to a particular event may indicate demographic traits that are likely true, such that outliers may be removed from the set or considered at a reduced weight. Negative correlations may indicate that demographic information within a source set, such as the online measurement data, may be false or suspect.

Abstract translation: 本公开提供了用于增强观众测量数据的系统和方法。 离线和在线观众测量数据可以进行比较和相关，以提高每个数据和源集的质量。 与特定事件相关的离线和在线数据集之间的正相关可以指示可能是真实的人口统计学特征，使得异常值可以从集合中移除或以减小的权重考虑。 负相关可能表明源集合中的人口统计信息（如在线测量数据）可能是假的或可疑的。

公开(公告)号：US20150161654A1

公开(公告)日：2015-06-11

申请号：US14103453

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Edward Little ,  Bozhena Bidyuk ,  Chao Cai ,  Todd Morris Jackson ,  John Chih Chang Huang

IPC: G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating rules for assigning attribution credit across events, includes, identifying, by a processor, conversions at a website. The processor identifies path types associated with the conversions. Each path type identifies events and a index position indicating an event's relative position. The processor identifies a subset of the identified path types to be rewritten according to a path rewriting policy. The processor then rewrites the identified subset of the identified path types as rewritten path types. The processor determines, for each of the rewritten path types and remaining identified path types associated with the identified conversions, attribution credits for each event included in the path type. The processor creates, for each of the rewritten path types and remaining identified path types associated with the identified conversions, a rule for assigning the determined attribution credit to each event of the path type for which the rule is created.

Abstract translation: 用于创建用于在事件之间分配归因信用的规则的系统和方法，包括由处理器识别网站上的转化。 处理器识别与转换相关联的路径类型。 每个路径类型标识事件和指示事件的相对位置的索引位置。 处理器根据路径重写策略识别要重写的所识别的路径类型的子集。 然后，处理器将所识别的路径类型的所识别的子集重写为重写的路径类型。 处理器针对每个重写的路径类型以及与所识别的转换相关联的剩余识别的路径类型确定包括在路径类型中的每个事件的归因信用。 处理器为每个重写的路径类型和与所识别的转换相关联的剩余已识别的路径类型创建用于将确定的归因信用分配给创建规则的路径类型的每个事件的规则。

公开(公告)号：US08910195B1

公开(公告)日：2014-12-09

申请号：US14185534

申请日：2014-02-20

Applicant: Google Inc.

Inventor： David Barney ,  Chao Cai ,  Timothy Wright ,  William Patrick Kee

IPC: H04H60/32 ,  H04N21/442 ,  H04N21/258

CPC classification number: H04N21/44213 ,  H04H60/31 ,  H04H60/45 ,  H04H60/66 ,  H04N21/25883

Abstract: The present disclosure provides systems and methods for enhancing audience measurement data. Offline and online audience measurement data may be compared and correlated to improve the quality of each data and source set. Positive correlations between the offline and online data sets related to a particular event may indicate demographic traits that are likely true, such that outliers may be removed from the set or considered at a reduced weight. Negative correlations may indicate that demographic information within a source set, such as the online measurement data, may be false or suspect.

Abstract translation: 本公开提供了用于增强观众测量数据的系统和方法。 离线和在线观众测量数据可以进行比较和相关，以提高每个数据和源集的质量。 与特定事件相关的离线和在线数据集之间的正相关可以指示可能是真实的人口统计学特征，使得异常值可以从集合中移除或以减小的权重考虑。 负相关可能表明源集合中的人口统计信息（如在线测量数据）可能是假的或可疑的。

公开(公告)号：US09852440B2

公开(公告)日：2017-12-26

申请号：US14103487

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Bozhena Bidyuk ,  Stefan Schnabl ,  Richard Edward Little ,  Chao Cai ,  David Earl Barney ,  William Patrick Kee

IPC: G06Q30/00 ,  G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for selecting content for display at a device includes, identifying by a processor, a visitor identifier associated with a device on which to display content. The processor can identify a path associated with the visitor identifier. The path corresponding to a sequence of one or more events through which the visitor identifier has visited the website. The processor can identify a conversion probability of the identified path. The conversion probability of the identified path indicates a likelihood that the visitor identifier will convert at the website. The conversion probability of the identified path is a ratio of a number of conversions at the website to a number of visits to the website over a given time period. The processor can select content for display. The content selected based on the identified conversion probability of the identified path.

公开(公告)号：US20150161658A1

公开(公告)日：2015-06-11

申请号：US14103589

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Little ,  William Patrick Kee ,  Bozhena Bidyuk ,  Chao Cai ,  David Earl Barney ,  Stefan Schnabl

IPC: G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating a data-driven attribution model are described. A processor identifies visits to a website. The processor identifies a path for each visitor identifier associated with the visits. The processor determines, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion. The processor calculates, for each of a plurality of the path types, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated. The processor determines, for each event, an attribution credit based on the calculated counterfactual gain of the event. The processor then stores the attribution credits of each of the events.

Abstract translation: 描述了用于创建数据驱动归因模型的系统和方法。 处理器识别对网站的访问。 处理器识别与访问相关联的每个访问者标识符的路径。 对于与所识别的路径相关联的每个路径类型，处理器基于与导致转换的路径类型相对应的访问次数来确定路径类型转换概率。 对于多个路径类型中的每一个，处理器基于给定路径类型的转换概率和不包括反事实增益的事件的路径类型的转换概率来计算每个事件的每个事件的反事实增益 计算。 处理器根据事件的反事实增益确定每个事件的归因信用。 然后处理器存储每个事件的归因信用。