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    Image relevance model
    1.
    发明授权
    Image relevance model 有权
    图像相关模型

    公开(公告)号：US09176988B2

    公开(公告)日：2015-11-03

    申请号：US13966737

    申请日：2013-08-14

    申请人： Google Inc.

    发明人： Samy Bengio ,  Erik Murphy-Chutorian ,  Yangli Hector Yee ,  Charles J. Rosenberg

    IPC分类号： G06K9/66 ,  G06K9/62 ,  G06K9/60 ,  G06K9/54 ,  G06F17/30

    CPC分类号： G06F17/30256 ,  G06F17/30271 ,  G06K9/6223 ,  G06K9/6262

    摘要： Methods, systems, and apparatus, including computer program products, for identifying images relevant to a query are disclosed. An image search subsystem selects images to reference in image search results that are responsive to a query based on an image relevance model that is trained for the query. An independent image relevance model is trained for each unique query that is identified by the image search subsystem. The image relevance models can be applied to images to order image search results obtained for the query. Each relevance model is trained based on content feature values of images that are identified as being relevant to the query (e.g., frequently selected from the image search results) and images that are identified as being relevant to another unique query. The trained model is applied to the content feature values of all known images to generate an image relevance score that can be used to order search results for the query.

    摘要翻译： 公开了用于识别与查询相关的图像的方法，系统和装置，包括计算机程序产品。 图像搜索子系统基于针对查询进行训练的图像相关性模型，在响应于查询的图像搜索结果中选择图像进行参考。 对由图像搜索子系统识别的每个唯一查询训练独立的图像相关性模型。 图像相关性模型可以应用于图像以订购为查询获得的图像搜索结果。 基于被识别为与查询相关（例如，从图像搜索结果中频繁选择）的图像的内容特征值以及被识别为与另一唯一查询相关的图像来训练每个相关性模型。 经过训练的模型被应用于所有已知图像的内容特征值，以生成可用于对查询进行搜索结果的图像相关性分数。

    Customizing image search for user attributes
    2.
    发明授权
    Customizing image search for user attributes 有权
    自定义图像搜索用户属性

    公开(公告)号：US08782029B1

    公开(公告)日：2014-07-15

    申请号：US13959233

    申请日：2013-08-05

    申请人： Google Inc.

    发明人： Yangli Hector Yee ,  Charles J. Rosenberg

    IPC分类号： G06F17/30 ,  G06F7/00

    CPC分类号： G06F17/30864 ,  G06F17/30244 ,  G06F17/30268 ,  G06F17/3053

    摘要： Systems, method, and apparatus including computer program products for providing image search results. In some implementations, a method is provided. The method includes receiving from a user a query for images including static images, moving images, and images within multimedia content, identifying at least one of a language attribute and a locale attribute of the user, generating multiple search results, each result corresponding to an image content item that satisfies the query, ordering the search results based at least on click data for image content items that satisfy the query, the click data gathered from users having at least one of the language attribute and the locale attribute, and presenting the ordered search results to the user, including presenting representations of the corresponding image content items.

    摘要翻译： 包括用于提供图像搜索结果的计算机程序产品的系统，方法和装置。 在一些实现中，提供了一种方法。 该方法包括从用户接收包括静态图像，运动图像和多媒体内容中的图像的图像的查询，识别用户的语言属性和区域设置属性中的至少一个，生成多个搜索结果，每个结果对应于 满足查询的图像内容项目，至少基于满足查询的图像内容项目的点击数据，从具有语言属性和语言环境属性中的至少一个的用户收集的点击数据来排序搜索结果，并呈现订购的图像内容项目 搜索结果给用户，包括呈现对应的图像内容项目的表示。

    Image classification
    4.
    发明授权
    Image classification 有权
    图像分类

    公开(公告)号：US09183226B2

    公开(公告)日：2015-11-10

    申请号：US14336692

    申请日：2014-07-21

    申请人： Google Inc.

    发明人： Yangli Hector Yee ,  Samy Bengio ,  Charles J. Rosenberg ,  Erik Murphy-Chutorian

    IPC分类号： G06K9/62 ,  G06K9/46 ,  G06K9/66 ,  G06K9/54 ,  G06K9/60 ,  G06F17/30

    CPC分类号： G06F17/30253 ,  G06F17/30244 ,  G06F17/30864 ,  G06K9/4676 ,  G06K9/6256 ,  G06K9/66 ,  G06K2209/01

    摘要： An image classification system trains an image classification model to classify images relative to text appearing with the images. Training images are iteratively selected and classified by the image classification model according to feature vectors of the training images. An independent model is trained for unique n-grams of text. The image classification system obtains text appearing with an image and parses the text into candidate labels for the image. The image classification system determines whether an image classification model has been trained for the candidate labels. When an image classification model corresponding to a candidate label has been trained, the image classification subsystem classifies the image relative to the candidate label. The image is labeled based on candidate labels for which the image is classified as a positive image.

    摘要翻译： 图像分类系统训练图像分类模型，以便相对于与图像一起出现的文本来分类图像。 根据训练图像的特征向量，通过图像分类模型迭代地选择和分类训练图像。 对独特的n克文本进行了独立的模型训练。 图像分类系统获得与图像一起出现的文本，并将文本解析为图像的候选标签。 图像分类系统确定是否针对候选标签训练了图像分类模型。 当对应于候选标签的图像分类模型已经被训练时，图像分类子系统将图像相对于候选标签进行分类。 基于将图像分类为正图像的候选标签来标记图像。

    Refining image relevance models
    5.
    发明授权
    Refining image relevance models 有权
    精炼图像相关模型

    公开(公告)号：US09177046B2

    公开(公告)日：2015-11-03

    申请号：US14543312

    申请日：2014-11-17

    申请人： Google Inc.

    发明人： Arcot J. Preetham ,  Thomas J. Duerig ,  Charles J. Rosenberg ,  Yangli Hector Yee ,  Samy Bengio

    IPC分类号： G06K9/62 ,  G06F17/30 ,  G06K9/66 ,  G06K9/52

    CPC分类号： G06F17/30675 ,  G06F17/3028 ,  G06K9/52 ,  G06K9/6202 ,  G06K9/6256 ,  G06K9/6262 ,  G06K9/6296 ,  G06K9/66

    摘要： Methods, systems and apparatus for refining image relevance models. In general, one aspect of the subject matter described in this specification can be implemented in methods that include re-training an image relevance model by generating a first re-trained model based on content feature values of first images of a first portion of training images in a set of training images, receiving, from the first re-trained model, image relevance scores for second images of a second portion of the set of training images, removing, from the set of training images, some of the second images identified as outlier images for which the image relevance score received from the first re-trained model is below a threshold score, and generating a second re-trained model based on content feature values of the first images of the first portion and the second images of the second portion that remain following removal of the outlier images.

    摘要翻译： 图像相关模型的方法，系统和装置。 通常，本说明书中描述的主题的一个方面可以以包括通过基于训练图像的第一部分的第一图像的内容特征值生成第一重新训练的模型来重新训练图像相关性模型的方法来实现 在一组训练图像中，从所述第一重新训练的模型中接收所述训练图像集合的第二部分的第二图像的图像相关性分数，从所述训练图像集合中去除被识别为 从第一重新训练的模型接收的图像相关性得分低于阈值分数的异常值图像，并且基于第一部分的第一图像和第二图像的第二图像的内容特征值生成第二重新训练的模型 删除离群图像后仍保留的部分。

    METHODS, SYSTEMS, AND MEDIA FOR RECOMMENDING CONTENT ITEMS BASED ON TOPICS
    6.
    发明申请
    METHODS, SYSTEMS, AND MEDIA FOR RECOMMENDING CONTENT ITEMS BASED ON TOPICS 审中-公开

    公开(公告)号：US20170103343A1

    公开(公告)日：2017-04-13

    申请号：US15384692

    申请日：2016-12-20

    申请人： Google Inc.

    发明人： Yangli Hector Yee ,  James Vincent McFadden ,  John Kraemer ,  Dasarathi Sampath

    IPC分类号： G06N99/00 ,  G06F17/30 ,  G06N7/00

    CPC分类号： G06N20/00 ,  G06F16/24578 ,  G06F16/248 ,  G06F16/335 ,  G06F16/70 ,  G06F16/951 ,  G06N3/0472 ,  G06N7/005

    摘要： Mechanisms for recommending content items based on topics are provided. In some implementations, a method for recommending content items is provided that includes: determining a plurality of accessed content items associated with a user, wherein each of the plurality of content items is associated with a plurality of topics; determining the plurality of topics associated with each of the plurality of accessed content items; generating a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics; applying the model to determine, for a plurality of content items, a probability that the user would watch a content item of the plurality of content items; ranking the plurality of content items based on the determined probabilities; and selecting a subset of the plurality of content items to recommend to the user based on the ranked content items.

    Customizing image search for user attributes
    7.
    发明授权
    Customizing image search for user attributes 有权
    自定义图像搜索用户属性

    公开(公告)号：US09146997B2

    公开(公告)日：2015-09-29

    申请号：US14330185

    申请日：2014-07-14

    申请人： Google Inc.

    发明人： Yangli Hector Yee ,  Charles J. Rosenberg

    IPC分类号： G06F17/30 ,  G06F7/00

    CPC分类号： G06F17/30864 ,  G06F17/30244 ,  G06F17/30268 ,  G06F17/3053

    摘要： Systems, method, and apparatus including computer program products for providing image search results. In some implementations, a method is provided. The method includes receiving from a user a query for images including static images, moving images, and images within multimedia content, identifying at least one of a language attribute and a locale attribute of the user, generating multiple search results, each result corresponding to an image content item that satisfies the query, ordering the search results based at least on click data for image content items that satisfy the query, the click data gathered from users having at least one of the language attribute and the locale attribute, and presenting the ordered search results to the user, including presenting representations of the corresponding image content items.

    摘要翻译： 包括用于提供图像搜索结果的计算机程序产品的系统，方法和装置。 在一些实现中，提供了一种方法。 该方法包括从用户接收包括静态图像，运动图像和多媒体内容中的图像的图像的查询，识别用户的语言属性和区域设置属性中的至少一个，生成多个搜索结果，每个结果对应于 满足查询的图像内容项目，至少基于满足查询的图像内容项目的点击数据，从具有语言属性和语言环境属性中的至少一个的用户收集的点击数据来排序搜索结果，并呈现订购的图像内容项目 搜索结果给用户，包括呈现对应的图像内容项目的表示。

    CUSTOMIZING IMAGE SEARCH FOR USER ATTRIBUTES
    8.
    发明申请
    CUSTOMIZING IMAGE SEARCH FOR USER ATTRIBUTES 有权
    自定义用户属性的图像搜索

    公开(公告)号：US20150161258A1

    公开(公告)日：2015-06-11

    申请号：US14330185

    申请日：2014-07-14

    申请人： Google Inc.

    发明人： Yangli Hector Yee ,  Charles J. Rosenberg

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30864 ,  G06F17/30244 ,  G06F17/30268 ,  G06F17/3053

    摘要： Systems, method, and apparatus including computer program products for providing image search results. In some implementations, a method is provided. The method includes receiving from a user a query for images including static images, moving images, and images within multimedia content, identifying at least one of a language attribute and a locale attribute of the user, generating multiple search results, each result corresponding to an image content item that satisfies the query, ordering the search results based at least on click data for image content items that satisfy the query, the click data gathered from users having at least one of the language attribute and the locale attribute, and presenting the ordered search results to the user, including presenting representations of the corresponding image content items.

    摘要翻译： 包括用于提供图像搜索结果的计算机程序产品的系统，方法和装置。 在一些实现中，提供了一种方法。 该方法包括从用户接收包括静态图像，运动图像和多媒体内容中的图像的图像的查询，识别用户的语言属性和区域设置属性中的至少一个，生成多个搜索结果，每个结果对应于 满足查询的图像内容项目，至少基于满足查询的图像内容项目的点击数据，从具有语言属性和语言环境属性中的至少一个的用户收集的点击数据来排序搜索结果，并呈现订购的图像内容项目 搜索结果给用户，包括呈现对应的图像内容项目的表示。

    Image Relevance Model
    9.
    发明申请
    Image Relevance Model 有权
    图像相关性模型

    公开(公告)号：US20150161172A1

    公开(公告)日：2015-06-11

    申请号：US13966737

    申请日：2013-08-14

    申请人： Google Inc

    发明人： Samy Bengio ,  Erik Murphy-Chutorian ,  Yangli Hector Yee ,  Charles J. Rosenberg

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30256 ,  G06F17/30271 ,  G06K9/6223 ,  G06K9/6262

    摘要： Methods, systems, and apparatus, including computer program products, for identifying images relevant to a query are disclosed. An image search subsystem selects images to reference in image search results that are responsive to a query based on an image relevance model that is trained for the query. An independent image relevance model is trained for each unique query that is identified by the image search subsystem. The image relevance models can be applied to images to order image search results obtained for the query. Each relevance model is trained based on content feature values of images that are identified as being relevant to the query (e.g., frequently selected from the image search results) and images that are identified as being relevant to another unique query. The trained model is applied to the content feature values of all known images to generate an image relevance score that can be used to order search results for the query.

    摘要翻译： 公开了用于识别与查询相关的图像的方法，系统和装置，包括计算机程序产品。 图像搜索子系统基于针对查询进行训练的图像相关性模型，在响应于查询的图像搜索结果中选择图像进行参考。 对由图像搜索子系统识别的每个唯一查询训练独立的图像相关性模型。 图像相关性模型可以应用于图像以订购为查询获得的图像搜索结果。 基于被识别为与查询相关（例如，从图像搜索结果中频繁选择）的图像的内容特征值以及被识别为与另一唯一查询相关的图像来训练每个相关性模型。 经过训练的模型被应用于所有已知图像的内容特征值，以生成可用于对查询进行搜索结果的图像相关性分数。