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公开(公告)号：US09569696B1
公开(公告)日：2017-02-14
申请号：US14824561
申请日：2015-08-12
Applicant: YAHOO! INC.
Inventor： Simon Osindero
CPC classification number: G06K9/6256 , G06K9/00711 , G06K9/00718 , G06K9/00744 , G06K9/4671 , G06K9/6269 , G06K9/66 , G06K2009/4666
Abstract: Disclosed herein is an intelligent agent to analyze a media object. The agent comprises a trained model comprising a number of state layers for storing a history of actions taken by the agent in each of a number of previous iterations performed by the agent in analyzing a media object. The stored state may be used by the agent in a current iteration to determine whether or not to make, or abstain from making, a prediction from output generated by the model, identify another portion of the media object to analyze, end analysis. Output from the agent's model may comprise a semantic vector that can be mapped to a semantic vector space to identify a number of labels for a media object.
Abstract translation: 这里公开了一种用于分析媒体对象的智能代理。 代理包括训练模型，其包括多个状态层，用于存储代理在分析媒体对象时由代理执行的多个先前迭代中的每一个中采取的动作历史。 存储状态可以由代理在当前迭代中使用以确定是否对由模型生成的输出进行预测或者不做出，识别要分析的媒体对象的另一部分，结束分析。 来自代理模型的输出可以包括可被映射到语义向量空间以识别媒体对象的多个标签的语义向量。
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652.发明申请SYSTEM AND METHOD FOR CONTEXTUAL VIDEO ADVERTISEMENT SERVING IN GUARANTEED DISPLAY ADVERTISING 审中-公开用于保证展示广告服务的上下文视频广告系统和方法公开(公告)号：US20170032424A1
公开(公告)日：2017-02-02
申请号：US14815334
申请日：2015-07-31
Applicant: Yahoo! Inc.
Inventor： Suleyman Cetintas , Srinath Ravindran , Mohammad Saberian , Sandeep Soni , Kuang-chih Lee , Hong Yao , Jian Yang , Pradhan Pattanayak
IPC: G06Q30/02
CPC classification number: G06Q30/0269 , G06Q30/0277
Abstract: The technologies described herein serve contextually relevant advertisements under a guaranteed advertisement campaign. A publisher retrieves a guaranteed advertisement campaign related to a webpage available for serving an advertisement, and identifies a set of advertisements relating to the guaranteed advertisement campaign. Advertisement selecting circuitry of the publisher determines whether an advertisement that is contextually relevant to content published at the webpage is present in the set of advertisements. If there is no contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects an alternative advertisement from the set of advertisements that minimizes an under-delivery risk related to the guaranteed advertisement campaign. If there is a contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects the contextually relevant advertisement. Then, the publisher provides the selected advertisement to a client device.
Abstract translation: 本文描述的技术在保证的广告活动下提供与内容相关的广告。 发布者检索与可用于服务广告的网页有关的保证广告活动，并且识别与保证广告活动相关的一组广告。 发布者的广告选择电路决定在该广告集中是否存在与在网页上发布的内容上下文相关的广告。 如果广告集合中没有上下文相关的广告，则广告选择电路从该广告集合中选择一个替代的广告，使与保证的广告活动相关的不足的风险最小化。 如果广告集合中存在上下文相关的广告，则广告选择电路选择上下文相关的广告。 然后，发布者将所选择的广告提供给客户端设备。
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公开(公告)号：US20170031654A1
公开(公告)日：2017-02-02
申请号：US15289323
申请日：2016-10-10
Applicant: Yahoo! Inc.
Inventor： Maria Renhui Zhang , Nicholas D'Aloisio-Montilla , Qichu Lu
CPC classification number: G06F7/08 , G06F16/24578 , G06F16/3323 , G06F16/345 , G06F16/353 , G06F16/41 , G06Q10/0639 , G06Q30/02
Abstract: Embodiments of the present disclosure may be used to gather, rank, categorize, and perform other processing of various types of content. In some embodiments, content items such as text, images, video, and other content are received from a variety of different sources and are processed to generate an article containing selected content items. While there may be hundreds or thousands of separate articles and stories regarding a particular topic, embodiments of the present disclosure help provide users with a single concise article that contains high-quality content items selected from among a potentially vast number of disparate sources.
Abstract translation: 本公开的实施例可以用于收集，排序，分类和执行各种类型的内容的其他处理。 在一些实施例中，从各种不同的来源接收诸如文本，图像，视频和其他内容的内容项目，并被处理以生成包含所选内容项目的文章。 虽然可能存在关于特定主题的数百或数千个独立的文章和故事，但是本公开的实施例有助于向用户提供包含从潜在的大量不同来源中选出的高质量内容项的单一简洁的文章。
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公开(公告)号：US09558180B2
公开(公告)日：2017-01-31
申请号：US14147001
申请日：2014-01-03
Applicant: Yahoo! Inc.
Inventor： Maria Renhui Zhang , Nicholas D'Aloisio-Montilla , Qichu Lu
CPC classification number: G06F17/30705 , G06F17/278 , G06F17/30241 , G06F17/30424 , G06F17/3053 , G06F17/30675 , G06F17/30684 , G06F17/30696 , G06F17/30769 , G06F17/30864
Abstract: Embodiments of the present disclosure may be utilized to analyze a content item comprising text to identify: a quote, a named entity that is the source of the quote (e.g., a person or organization such as a company), and identification information for the named entity (such as a title of the person giving the quote). Quotes may also be ranked to determine, for example, the best quotes to include in an article.
Abstract translation: 本公开的实施例可以用于分析包括文本的内容项目，以识别：报价，作为报价源的命名实体（例如，诸如公司的个人或组织）以及用于指定的 实体（如提供报价的人的标题）。 报价也可能被排名以确定例如在文章中包含的最佳报价。
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公开(公告)号：US20160378858A1
公开(公告)日：2016-12-29
申请号：US15261546
申请日：2016-09-09
Applicant: Yahoo! Inc.
Inventor： Srinivas Vadrevu , Yi Chang , Zhaohui Zheng , Bo Long
IPC: G06F17/30
CPC classification number: G06F16/35 , G06F16/334 , G06F16/338 , G06F16/93
Abstract: One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.
Abstract translation: 一个特定实施例使用一个或多个聚类算法来聚集多个文档以获得一个或多个第一组聚类，其中：每个第一组聚类是使用聚类算法之一聚类文档而得到的; 并且对于每个第一组集合，每个文档属于来自第一组集合的集群之一; 访问搜索查询; 识别响应于搜索查询的搜索结果，其中搜索结果包括两个或更多个文档; 并且聚集搜索结果以获得第二组聚类，其中搜索结果的每个文档属于来自第二组聚类的聚类中的一个。
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Patent Agency Ranking
公开(公告)号：US20160364745A1
公开(公告)日：2016-12-15
申请号：US14734515
申请日：2015-06-09
Applicant: Yahoo! Inc.
Inventor： Yan He , Miao Chen , Maria Stone
IPC: G06Q30/02
Abstract: Online experimentation has been widely used to evaluate an effect of a new feature of an online product on user engagement. One challenge is that an existence of outliers can often complicate the analysis of such experimental results. Thus, a procedure is provided herein to detect and remove outliers from experimental results. The procedure can use statistical tests based on parametric distributions of sample maximum or minimum. These tests can be performed using an inward testing procedure to identify multiple outliers. Finally, these filtered test results can be used to control delivery of a new feature of an online product.
Abstract translation: 在线实验被广泛用于评估在线产品的新功能对用户参与的影响。 一个挑战是，异常值的存在往往会使这些实验结果的分析复杂化。 因此，本文提供了一种从实验结果中检测和去除异常值的过程。 该过程可以使用基于样本最大值或最小值的参数分布的统计检验。 这些测试可以使用向内测试程序进行，以识别多个异常值。 最后，这些过滤的测试结果可用于控制在线产品的新功能的传递。
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公开(公告)号：US20160364502A1
公开(公告)日：2016-12-15
申请号：US14739487
申请日：2015-06-15
Applicant: YAHOO! INC.
Inventor： Huming Wu , Shenhong Zhu
IPC: G06F17/30
CPC classification number: G06F17/30973 , G06F17/3053 , G06F17/30598 , G06F17/30867
Abstract: A seasonality-aware search assist identifies seasonal search query suggestions using seasonal information associated with the seasonal search query suggestions. A user's search query input, temporal information associated with the user's search query input and a seasonal information associated with each seasonal-aware search query suggestion candidates may be used to identify a number of seasonal search query suggestions for presentation to the user. Seasonal search query suggestion candidates may be promoted in a list of search query suggestions presented to the user, and any non-seasonal search query suggestions included in the list may be positioned below the seasonal search query suggestions in the list. A popularity score associated with each of the listed seasonal search query suggestions may be used to order the seasonal search query candidates, and a popularity score associated with each of the listed non-seasonal search query suggestions may be used to order the non-seasonal search query suggestions.
Abstract translation: 季节性感知搜索辅助使用与季节性搜索查询建议相关联的季节性信息来识别季节性搜索查询建议。 可以使用用户的搜索查询输入，与用户的搜索查询输入相关联的时间信息和与每个季节性感知搜索查询建议候选相关联的季节性信息来标识用于呈现给用户的季节性搜索查询建议的数量。 季节性搜索查询建议候选人可以在呈现给用户的搜索查询建议的列表中被提升，列表中包括的任何非季节性搜索查询建议可以位于列表中的季节性搜索查询建议之下。 可以使用与每个列出的季节性搜索查询建议相关联的流行度得分来排序季节性搜索查询候选者，并且可以使用与每个列出的非季节性搜索查询建议相关联的受欢迎程度来排序非季节性搜索 查询建议
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公开(公告)号：US09514216B2
公开(公告)日：2016-12-06
申请号：US14480528
申请日：2014-09-08
Applicant: Yahoo! Inc.
Inventor： Lei Duan , Fan Li , Srinivas Vadrevu , Emre Velipasaoglu , Swapnil Hajela , Deepayan Chakrabarti
CPC classification number: G06F17/30598 , G06F15/18 , G06F17/30873 , G06K9/6256 , G06N5/04 , G06N99/005 , G06Q10/10
Abstract: Exemplary methods and apparatuses are provided which may be used for classifying and indexing segmented portions of web pages and providing related information for use in information extraction and/or information retrieval systems. In an embodiment, an index of segmented portions may be used by a search engine to respond to a search query. In an embodiment, one or more machine learned models may be used to identify one or more feature properties of a plurality of segmented portions within one or more files, or otherwise inferable from the one or more files. In an embodiment, one or more machine learned models may be used to classify one or more of a plurality of segmented portions as being at least one of a plurality of segment types.
Abstract translation: 提供了可用于对网页的分段部分进行分类和索引并提供用于信息提取和/或信息检索系统的相关信息的示例性方法和装置。 在一个实施例中，搜索引擎可以使用分段部分的索引来响应搜索查询。 在一个实施例中，可以使用一个或多个机器学习模型来识别一个或多个文件内的多个分段部分的一个或多个特征属性，或者可以从一个或多个文件推断。 在一个实施例中，可以使用一个或多个机器学习模型来将多个分段部分中的一个或多个分类为多个分段类型中的至少一个。
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公开(公告)号：US20160350815A1
公开(公告)日：2016-12-01
申请号：US14761060
申请日：2015-05-29
Applicant: YAHOO! Inc.
Inventor： Angus Xianen Qiu , Haiyang Xu , Zhangang Lin
CPC classification number: G06Q30/0277 , G06Q30/0248
Abstract: The present teaching, which includes methods, systems and computer-readable media, relates to providing a representation of a relationship between entities related to online content interaction. The disclosed techniques may include receiving data related to online content interactions between a set of first entities and a set of second entities, and based on the received data, determining, for each one of the set of first entities, a set of first interaction frequency values each corresponding to one of the set of second entities, and determining, for each one of the set of second entities, a second interaction frequency value. Further, for each one of the set of first entities, a set of relation values may be determined based on the set of first interaction frequency values for that first entity and the second interaction frequency values, each relation value indicating an interaction relationship between that first entity and one second entity.
Abstract translation: 包括方法，系统和计算机可读介质的本教导涉及提供与在线内容交互相关的实体之间的关系的表示。 所公开的技术可以包括接收与一组第一实体和一组第二实体之间的在线内容交互有关的数据，并且基于所接收的数据，为该组第一实体中的每一个确定一组第一交互频率 每个对应于该组第二实体中的一个的值，以及为该组第二实体中的每一个确定第二相互作用频率值。 此外，对于该组第一实体中的每一个，可以基于该第一实体的第一相互作用频率值集合和第二相互作用频率值来确定一组关系值，每个关系值表示该第一实体之间的相互作用关系 实体和一个第二实体。
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