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1.发明申请公开(公告)号：US20170061014A1
公开(公告)日：2017-03-02
申请号：US14841078
申请日：2015-08-31
Applicant: Google Inc.
Inventor： Matthias Heiler , Michael Schaer , Nikola Todorovic , Robin Nittka , Thomas Fischbacher , Laura Dragoi
IPC: G06F17/30
CPC classification number: G06F17/30867 , G06F17/30528
Abstract: A system and method for providing a search experience in which users are protected from exposure to inappropriate offensive or sensitive content is described. A search system may classify a search query and candidate search results obtained in response to the search query. Based on the classification of the search query and search results, the candidate search results may be modified to generate a set of search results presented to a user such that the presented search results do not include inappropriate sensitive or offensive content.
Abstract translation: 描述了一种用于提供用户被保护以免暴露于不适当的冒犯或敏感内容的搜索体验的系统和方法。 搜索系统可以对搜索查询和响应于搜索查询获得的候选搜索结果进行分类。 基于搜索查询和搜索结果的分类，可以修改候选搜索结果以生成呈现给用户的一组搜索结果，使得呈现的搜索结果不包括不适当的敏感或令人反感的内容。
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公开(公告)号：US20150186796A1
公开(公告)日：2015-07-02
申请号：US14143192
申请日：2013-12-30
Applicant: GOOGLE INC.
Inventor： Thomas Fischbacher
IPC: G06N99/00
CPC classification number: G06N99/005 , G06F19/24
Abstract: Described is a machine learning system for binary classifications. The system improves interpolation schemes used in isotonic regressions by providing a continuous function that also is monotonic. The system outputs a probability estimating function on a signal space that is both monotonic and varies continuously with the input signals. More specifically, described is an interpolation function that is continuous and piecewise linear on Delaunay simplices. Accordingly, the resulting probability estimation function may more accurately match actual probabilities especially when training data is sparse.
Abstract translation: 描述了二进制分类的机器学习系统。 该系统通过提供也是单调的连续函数来改进在等渗回归中使用的插值方案。 该系统在信号空间上输出概率估计函数，该信号空间既单调又与输入信号连续变化。 更具体地说，描述了一种在Delaunay简单的连续和分段线性的插值函数。 因此，所得到的概率估计函数可以更准确地匹配实际概率，特别是当训练数据稀疏时。
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3.发明授权Interpolating isotonic regression for binary classification of spam, explicit material or malware using interpolation based on a Delaunay triangulation 有权使用Delaunay三角测量法进行内插的垃圾邮件，显式材料或恶意软件二进制分类的插值等渗回归公开(公告)号：US09189752B2
公开(公告)日：2015-11-17
申请号：US14143192
申请日：2013-12-30
Applicant: Google Inc.
Inventor： Thomas Fischbacher
CPC classification number: G06N99/005 , G06F19/24
Abstract: Described is a machine learning system for binary classifications. The system improves interpolation schemes used in isotonic regressions by providing a continuous function that also is monotonic. The system outputs a probability estimating function on a signal space that is both monotonic and varies continuously with the input signals. More specifically, described is an interpolation function that is continuous and piecewise linear on Delaunay simplices. Accordingly, the resulting probability estimation function may more accurately match actual probabilities especially when training data is sparse.
Abstract translation: 描述了二进制分类的机器学习系统。 该系统通过提供也是单调的连续函数来改进在等渗回归中使用的插值方案。 该系统在信号空间上输出概率估计函数，该信号空间既单调又与输入信号连续变化。 更具体地说，描述了一种在Delaunay简单的连续和分段线性的插值函数。 因此，所得到的概率估计函数可以更准确地匹配实际概率，特别是当训练数据稀疏时。
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