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：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：US09852439B2

公开(公告)日：2017-12-26

申请号：US14103440

申请日：2013-12-11

Applicant: Google Inc.

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

IPC: G06Q30/02

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

Abstract: Systems and methods for measuring conversion probabilities of a path types for an attribution model includes, identifying by a processor, paths taken by visitors to visit a website. The paths correspond to a sequence of events that cause a visitor to visit the website. The processor can identify as paths, for each path, subpaths corresponding to each visit to the website. The processor computes a total path count for each path type. The processor identifies, for each path type, a conversion path count indicating a number of paths taken by visitors that resulted in a conversion at the website. The processor calculates, for each path type, a probability of conversion and then provides the calculated probability of conversion for a given path type for an attribution model used in assigning attribution credit to events of a path.

公开(公告)号：US20170068720A1

公开(公告)日：2017-03-09

申请号：US14846369

申请日：2015-09-04

Applicant: Google Inc.

Inventor： Jeongwoo Ko ,  Frank Uyeda ,  Arturo Ruiz, II ,  Bozhena Bidyuk

IPC: G06F17/30

CPC classification number: G06F16/285 ,  G06F16/24575 ,  G06F16/3331 ,  G06F16/353 ,  G06F16/951 ,  G06F16/9535

Abstract: An analytics engine for determining analytic relationships in data queries based on responsive data sets includes a memory for storing data and a processor in communication with the memory. The processor is configured to identify a data query for analysis from a query repository, retrieve a plurality of interaction data associated with the data query, wherein the interaction data represents interactions between a plurality of user systems and a query result previously generated based on the data query, wherein the query result includes a plurality of links, identify a link selection count for each of the plurality of links based on the plurality of interaction data, classify the data query as one of a content targeting query and a data-creator targeting query based upon the plurality of link selection counts, and generate a query characteristic analysis based upon the classified data query and the plurality of link selection counts.

Abstract translation: 用于基于响应数据集确定数据查询中的分析关系的分析引擎包括用于存储数据的存储器和与存储器通信的处理器。 处理器被配置为从查询库识别用于分析的数据查询，检索与数据查询相关联的多个交互数据，其中交互数据表示多个用户系统之间的交互和基于数据先前生成的查询结果 查询，其中所述查询结果包括多个链接，基于所述多个交互数据来识别所述多​​个链接中的每一个的链接选择计数，将所述数据查询分类为内容定向查询和数据创建者定位查询之一 基于所述多个链接选择计数，并且基于所述分类数据查询和所述多个链接选择计数生成查询特征分析。

公开(公告)号：US20150161655A1

公开(公告)日：2015-06-11

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: G06Q30/02

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.

Abstract translation: 用于选择用于在设备上显示的内容的系统和方法包括：由处理器识别与其上显示内容的设备相关联的访问者标识符。 处理器可以识别与访问者标识符相关联的路径。 对应于访问者标识符访问了该网站的一个或多个事件的序列的路径。 处理器可以识别所识别的路径的转换概率。 所识别的路径的转换概率表示访问者标识符将在网站上转换的可能性。 所识别的路径的转换概率是网站上的转化次数与给定时间段内对网站的访问次数的比率。 处理器可以选择要显示的内容。 基于识别的路径的所识别的转换概率来选择内容。

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。

公开(公告)号：US20150161657A1

公开(公告)日：2015-06-11

申请号：US14103440

申请日：2013-12-11

Applicant: Google Inc.

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

IPC: G06Q30/02

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

Abstract: Systems and methods for measuring conversion probabilities of a path types for an attribution model includes, identifying by a processor, paths taken by visitors to visit a website. The paths correspond to a sequence of events that cause a visitor to visit the website. The processor can identify as paths, for each path, subpaths corresponding to each visit to the website. The processor computes a total path count for each path type. The processor identifies, for each path type, a conversion path count indicating a number of paths taken by visitors that resulted in a conversion at the website. The processor calculates, for each path type, a probability of conversion and then provides the calculated probability of conversion for a given path type for an attribution model used in assigning attribution credit to events of a path.

Abstract translation: 用于衡量归因模型的路径类型的转换概率的系统和方法包括由处理器识别访问者访问网站所采取的路径。 这些路径对应于导致访问者访问网站的一系列事件。 处理器可以为每个路径识别与对网站的每次访问相对应的子路径。 处理器计算每个路径类型的总路径计数。 处理器为每个路径类型识别一个转化路径计数，指示访问者在网站上进行转换所花费的路径数。 处理器为每个路径类型计算转换概率，然后为给定路径类型提供所计算的转换概率，用于为归属信用分配路径事件中使用的归属模型。