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    • 72. 发明授权
    • Selecting an algorithm for identifying similar user identifiers based on predicted click-through-rate
    • 基于预测的点击率选择用于识别类似用户标识符的算法
    • US08886575B1
    • 2014-11-11
    • US13534480
    • 2012-06-27
    • Jia LiuYijian BaiManojav PatilDeepak RavichandranSittichai JiampojamarnShankar Ponnekanti
    • Jia LiuYijian BaiManojav PatilDeepak RavichandranSittichai JiampojamarnShankar Ponnekanti
    • G06F15/18
    • G06Q30/0201
    • A computerized method, system for, and computer-readable medium operable to select an algorithm for generating models configured to identify similar user identifiers. A first plurality of models generated by a first algorithm is received. A plurality of lists of similar user identifiers is generated. User queries associated with user identifiers on the plurality of lists of similar user identifiers are identified. Predicted click-through rates for the user queries is received. An average predicted click-through rate is computed for each model based on the predicted click-through rates. A weighted average predicted click-through rate associated with the first plurality of models is computed. The weighted average predicted click-through rate for the first plurality of models can be compared to a weighted average predicted click-through rate for a second plurality of models generated by a second algorithm. The algorithm for generating models is selected based on the comparison.
    • 一种计算机化方法,系统和计算机可读介质,其可操作以选择用于生成被配置为识别相似用户标识符的模型的算法。 接收由第一算法生成的第一多个模型。 生成多个相似用户标识符的列表。 识别与多个相似用户标识符列表上的用户标识符相关联的用户查询。 收到用户查询的预测点击率。 根据预测的点击率计算每个模型的平均预测点击率。 计算与第一多个模型相关联的加权平均预测点击率。 可以将第一多个模型的加权平均预测点击率与由第二算法生成的第二多个模型的加权平均预测点击率进行比较。 基于比较选择生成模型的算法。
    • 75. 发明授权
    • Image-based CAPTCHA exploiting context in object recognition
    • 基于图像的CAPTCHA利用对象识别中的上下文
    • US08483518B2
    • 2013-07-09
    • US12709311
    • 2010-02-19
    • Bin ZhuJia LiuQiujie LiShipeng LiNing Xu
    • Bin ZhuJia LiuQiujie LiShipeng LiNing Xu
    • G06K9/60
    • G06F21/36G06F17/30247G06T7/11G06T7/194G06T11/60G06T2210/22
    • Techniques for an image-based CAPTCHA for object recognition are described. The disclosure describes adding images to a database by collecting images by querying descriptive keywords to an image search engine or crawling images from the Internet.The disclosure describes generating the image-based CAPTCHA. The image is retrieved from the database, along with objects having significant values. An object is cropped from its image. The portion on the image where the object has been cropped is filled with image inpainting. The process obtains other objects from the database. The object is mixed among the other objects to form a set of candidate objects. A user is asked to select “the object” from the set of candidate objects that fits or matches the image. The image-based CAPTCHA evaluates whether a response, the selection, is from a human or a bot.
    • 描述了用于对象识别的基于图像的CAPTCHA的技术。 本公开内容描述了通过向图像搜索引擎查询描述性关键词或从因特网爬行图像来收集图像来向图像数据库添加图像。 该公开内容描述了生成基于图像的CAPTCHA。 从数据库中检索图像以及具有重要值的对象。 一个物体从其图像中裁剪出来。 被裁剪对象的图像部分填充有图像修复。 该进程从数据库获取其他对象。 对象在其他对象之间进行混合以形成一组候选对象。 要求用户从适合或匹配图像的候选对象集中选择“对象”。 基于图像的CAPTCHA评估响应,选择是来自人还是机器人。
    • 78. 发明申请
    • Image-Based CAPTCHA Exploiting Context in Object Recognition
    • 基于图像的CAPTCHA探索对象识别中的上下文
    • US20110208716A1
    • 2011-08-25
    • US12709311
    • 2010-02-19
    • Jia LiuBin Benjamin ZhuQiujie LiShipeng LiNing Xu
    • Jia LiuBin Benjamin ZhuQiujie LiShipeng LiNing Xu
    • G06F17/30G06K9/00
    • G06F21/36G06F17/30247G06T7/11G06T7/194G06T11/60G06T2210/22
    • Techniques for an image-based CAPTCHA for object recognition are described. The disclosure describes adding images to a database by collecting images by querying descriptive keywords to an image search engine or crawling images from the Internet.The disclosure describes generating the image-based CAPTCHA. The image is retrieved from the database, along with objects having significant values. An object is cropped from its image. The portion on the image where the object has been cropped is filled with image inpainting. The process obtains other objects from the database. The object is mixed among the other objects to from a set of candidate objects. A user is asked to select “the object” from the set of candidate objects that fits or matches the image. The image-based CAPTCHA evaluates whether a response, the selection, is from a human or a bot.
    • 描述了用于对象识别的基于图像的CAPTCHA的技术。 本公开内容描述了通过向图像搜索引擎查询描述性关键词或从因特网爬行图像来收集图像来向图像数据库添加图像。 该公开内容描述了生成基于图像的CAPTCHA。 从数据库中检索图像以及具有重要值的对象。 一个物体从其图像中裁剪出来。 被裁剪对象的图像部分填充有图像修复。 该进程从数据库获取其他对象。 该对象在其他对象之间从一组候选对象中进行混合。 要求用户从适合或匹配图像的候选对象集中选择“对象”。 基于图像的CAPTCHA评估响应,选择是来自人还是机器人。
    • 80. 发明申请
    • HIGH-CAPACITANCE AND LOW-OXYGEN POROUS CARBON FOR EDLCS
    • 用于EDLCS的高电容和低氧多孔碳
    • US20110183841A1
    • 2011-07-28
    • US12970028
    • 2010-12-16
    • Kishor Purushottam GadkareeJia Liu
    • Kishor Purushottam GadkareeJia Liu
    • C01B31/08C01B31/12
    • H01G11/34C01B32/30C01B32/342H01G11/44H01M4/625H01M4/8673Y02E60/13
    • A method for producing a low oxygen content activated carbon material includes heating a natural, non-lignocellulosic carbon precursor in an inert or reducing atmosphere to form a first carbon material, mixing the first carbon material with an inorganic compound to form an aqueous mixture, heating the aqueous mixture in an inert or reducing atmosphere to incorporate the inorganic compound into the first carbon material, removing the inorganic compound from the first carbon material to produce a second carbon material, and heating the second carbon material in an inert or reducing atmosphere to form the low oxygen content activated carbon material. The activated carbon material is suitable to form improved carbon-based electrodes for use in high energy density devices.
    • 一种生产低氧含量活性炭材料的方法包括在惰性或还原性气氛中加热天然的非木质纤维素碳前体以形成第一碳材料,将第一碳材料与无机化合物混合以形成含水混合物,加热 所述含水混合物在惰性或还原气氛中将所述无机化合物掺入到所述第一碳材料中,从所述第一碳材料中除去所述无机化合物以产生第二碳材料,并在惰性或还原性气氛中加热所述第二碳材料以形成 低氧含量的活性炭材料。 活性炭材料适用于形成用于高能量密度装置的改进的碳基电极。