公开(公告)号：US09195997B2

公开(公告)日：2015-11-24

申请号：US14152228

申请日：2014-01-10

Applicant: Google Inc.

Inventor： Nikola Jevtic ,  Zhaosheng (Josh) Bao ,  William David Reardon ,  Max David Cohen

IPC: G06Q30/00 ,  G06Q30/02

CPC classification number: G06Q30/0277 ,  G06Q10/0639 ,  G06Q30/0243

Abstract: Systems, methods, and computer-readable storage media that may be used to generate representative sample images for content campaigns are provided. One method includes identifying a resource in which a content campaign item has been previously displayed. The method further includes determining a content slot within the resource in which the content campaign item was previously displayed. The content slot is determined based on a slot signature associated with the content slot. The method further includes retrieving a current version of the resource, where the current version of the resource includes a current content item appearing in the content slot. The method further includes generating a representative image of the resource that includes the content campaign item by replacing the current content item appearing in the content slot within the current version of the resource with the content campaign item.

Abstract translation: 提供了可用于为内容活动产生代表性样本图像的系统，方法和计算机可读存储介质。 一种方法包括识别其中先前显示内容活动项目的资源。 该方法还包括确定内容广告系列项目之前显示的资源内的内容时隙。 基于与内容时隙相关联的时隙签名来确定内容时隙。 该方法还包括检索资源的当前版本，其中资源的当前版本包括出现在内容时隙中的当前内容项。 该方法还包括通过用内容广告活动项目代替在当前版本的资源内的内容时隙中出现的当前内容项目来生成包括内容活动项目的资源的代表图像。

公开(公告)号：US20140379743A1

公开(公告)日：2014-12-25

申请号：US14457869

申请日：2014-08-12

Applicant: Google Inc.

Inventor： Leonardo A. Laroco, Jr. ,  Nikola Jevtic ,  Nikolai V. Yakovenko ,  Jeffrey Reynar

IPC: G06F17/30

CPC classification number: G06F16/93 ,  G06F16/955 ,  G06N5/04 ,  G06N20/00

Abstract: A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.

公开(公告)号：US09760570B2

公开(公告)日：2017-09-12

申请号：US14300148

申请日：2014-06-09

Applicant: GOOGLE INC

Inventor： Leonardo A. Laroco, Jr. ,  Nikola Jevtic ,  Nikolai V. Yakovenko ,  Jeffrey Reynar

IPC: G06F17/30 ,  G06N5/04 ,  G06N99/00

CPC classification number: G06F17/30011 ,  G06F17/30876 ,  G06N5/04 ,  G06N99/005

Abstract: A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.

公开(公告)号：US20150199731A1

公开(公告)日：2015-07-16

申请号：US14152228

申请日：2014-01-10

Applicant: Google Inc.

Inventor： Nikola Jevtic ,  Zhaosheng (Josh) Bao ,  William David Reardon ,  Max David Cohen

IPC: G06Q30/02

CPC classification number: G06Q30/0277 ,  G06Q10/0639 ,  G06Q30/0243

Abstract: Systems, methods, and computer-readable storage media that may be used to generate representative sample images for content campaigns are provided. One method includes identifying a resource in which a content campaign item has been previously displayed. The method further includes determining a content slot within the resource in which the content campaign item was previously displayed. The content slot is determined based on a slot signature associated with the content slot. The method further includes retrieving a current version of the resource, where the current version of the resource includes a current content item appearing in the content slot. The method further includes generating a representative image of the resource that includes the content campaign item by replacing the current content item appearing in the content slot within the current version of the resource with the content campaign item.

Abstract translation: 提供了可用于为内容活动产生代表性样本图像的系统，方法和计算机可读存储介质。 一种方法包括识别其中先前显示内容活动项目的资源。 该方法还包括确定内容广告系列项目之前显示的资源内的内容时隙。 基于与内容时隙相关联的时隙签名来确定内容时隙。 该方法还包括检索资源的当前版本，其中资源的当前版本包括出现在内容时隙中的当前内容项。 该方法还包括通过用内容广告活动项目代替在当前版本的资源内的内容时隙中出现的当前内容项目来生成包括内容活动项目的资源的代表图像。

公开(公告)号：US20140289177A1

公开(公告)日：2014-09-25

申请号：US14300148

申请日：2014-06-09

Applicant: GOOGLE INC

Inventor： Leonardo A. Laroco, JR. ,  Nikola Jevtic ,  Nikolai V. Yakovenko ,  Jeffrey Reynar

IPC: G06N5/04 ,  G06N99/00

CPC classification number: G06F17/30011 ,  G06F17/30876 ,  G06N5/04 ,  G06N99/005

Abstract: A system and method for disambiguating references to entities in a document. In one embodiment, an iterative process is used to disambiguate references to entities in documents. An initial model is used to identify documents referring to an entity based on features contained in those documents. The occurrence of various features in these documents is measured. From the number occurrences of features in these documents, a second model is constructed. The second model is used to identify documents referring to the entity based on features contained in the documents. The process can be repeated, iteratively identifying documents referring to the entity and improving subsequent models based on those identifications. Additional features of the entity can be extracted from documents identified as referring to the entity.

Abstract translation: 一种用于消除文档中对实体的引用的系统和方法。 在一个实施例中，迭代过程用于消除对文档中对实体的引用。 初始模型用于根据这些文档中包含的特征来识别引用实体的文档。 测量这些文件中各种特征的出现情况。 从这些文件中的特征数出现，构建第二个模型。 第二个模型用于根据文档中包含的功能来识别引用该实体的文档。 该过程可以重复，迭代地识别参考实体的文档，并且基于这些标识来改进随后的模型。 实体的附加特征可以从标识为引用实体的文档中提取出来。