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    Framework for evaluating web search scoring functions
    4.
    发明授权
    Framework for evaluating web search scoring functions 有权
    评估网页搜索评分功能的框架

    公开(公告)号：US08060497B1

    公开(公告)日：2011-11-15

    申请号：US12508023

    申请日：2009-07-23

    Applicant: Misha Zatsman ,  Paul G. Haahr ,  Matthew D. Cutts ,  Yonghui Wu

    Inventor： Misha Zatsman ,  Paul G. Haahr ,  Matthew D. Cutts ,  Yonghui Wu

    IPC: G06F17/30

    CPC classification number: G06F17/30864

    Abstract: Methods, systems, and apparatus, including computer program products, for testing web search scoring functions. A query is received. A first and a second scoring function are selected by receiving search results responsive to the query; applying candidate scoring functions to the search results to determine scores for the search results for each candidate scoring function; identifying pairs of the candidate scoring functions, and calculating a diversity score for each of the pairs. A pair of candidate scoring functions is chosen from the one or more pairs of candidate scoring functions based on the diversity scores, and the alpha function is selected as the first scoring function and the beta function is selected as the second scoring function. The plurality of search results are presented in an order according to scores from the first scoring function and are presented in an order according to scores from the second scoring function.

    Abstract translation: 方法，系统和设备，包括计算机程序产品，用于测试网页搜索评分功能。 接收到查询。 通过接收响应于查询的搜索结果来选择第一和第二评分函数; 将候选评分函数应用于搜索结果以确定每个候选评分函数的搜索结果的分数; 识别候选评分函数的对，并且计算每个对的分集得分。 基于多样性分数从一个或多个候选评分函数对中选择一对候选评分函数，并且选择α函数作为第一评分函数，并且选择β函数作为第二评分函数。 多个搜索结果按照来自第一评分函数的分数的顺序呈现，并且根据来自第二评分函数的分数以顺序呈现。

    Framework for evaluating web search scoring functions
    6.
    发明授权
    Framework for evaluating web search scoring functions 有权
    评估网页搜索评分功能的框架

    公开(公告)号：US08572075B1

    公开(公告)日：2013-10-29

    申请号：US13296099

    申请日：2011-11-14

    Applicant: Misha Zatsman ,  Paul G. Haahr ,  Matthew D. Cutts ,  Yonghui Wu

    Inventor： Misha Zatsman ,  Paul G. Haahr ,  Matthew D. Cutts ,  Yonghui Wu

    IPC: G06F17/30

    CPC classification number: G06F17/30864

    Abstract: Methods, systems, and apparatus, including computer program products, for testing web search scoring functions. A query is received. A first and a second scoring function are selected by receiving search results responsive to the query; applying candidate scoring functions to the search results to determine scores for the search results for each candidate scoring function; identifying pairs of the candidate scoring functions, and calculating a diversity score for each of the pairs. A pair of candidate scoring functions is chosen from the one or more pairs of candidate scoring functions based on the diversity scores, and the alpha function is selected as the first scoring function and the beta function is selected as the second scoring function. The plurality of search results are presented in an order according to scores from the first scoring function and are presented in an order according to scores from the second scoring function.

    Abstract translation: 方法，系统和设备，包括计算机程序产品，用于测试网页搜索评分功能。 接收到查询。 通过接收响应于查询的搜索结果来选择第一和第二评分函数; 将候选评分函数应用于搜索结果以确定每个候选评分函数的搜索结果的分数; 识别候选评分函数的对，并且计算每个对的分集得分。 基于多样性分数从一个或多个候选评分函数对中选择一对候选评分函数，并且选择α函数作为第一评分函数，并且选择β函数作为第二评分函数。 多个搜索结果按照来自第一评分函数的分数的顺序呈现，并且根据来自第二评分函数的分数以顺序呈现。

    Personally identifiable information detection
    9.
    发明授权
    Personally identifiable information detection 有权

    公开(公告)号：US08561185B1

    公开(公告)日：2013-10-15

    申请号：US13109646

    申请日：2011-05-17

    Applicant: Muthuprasanna Muthusrinivasan ,  Paul Haahr ,  Matthew D. Cutts

    Inventor： Muthuprasanna Muthusrinivasan ,  Paul Haahr ,  Matthew D. Cutts

    IPC: G06F21/00

    CPC classification number: G06F21/6245 ,  G06F21/577 ,  H04L63/0823

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for privacy protection. In one aspect, a method includes accessing personally identifiable information (PII) type definitions that characterize PII types; identifying PII type information included in content of a web page, the PII type information being information matching at least one PII type definition; identifying secondary information included in the content of the web page, the secondary information being information that is predefined as being associated with PII type information; determining a risk score from the PII type information and the secondary information; and classifying the web page as a personal information exposure risk if the risk score meets a confidentiality threshold, wherein the personal information exposure risk is indicative of the web page including personally identifiable information.

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