LEARNING A DOCUMENT RANKING USING A LOSS FUNCTION WITH A RANK PAIR OR A QUERY PARAMETER
    1.
    发明申请
    LEARNING A DOCUMENT RANKING USING A LOSS FUNCTION WITH A RANK PAIR OR A QUERY PARAMETER 有权
    学习一个文件排序使用一个失败的功能与排名对或一个查询参数

    公开(公告)号:US20080027925A1

    公开(公告)日:2008-01-31

    申请号:US11460838

    申请日:2006-07-28

    IPC分类号: G06F17/30

    摘要: A method and system for generating a ranking function to rank the relevance of documents to a query is provided. The ranking system learns a ranking function from training data that includes queries, resultant documents, and relevance of each document to its query. The ranking system learns a ranking function using the training data by weighting incorrect rankings of relevant documents more heavily than the incorrect rankings of not relevant documents so that more emphasis is placed on correctly ranking relevant documents. The ranking system may also learn a ranking function using the training data by normalizing the contribution of each query to the ranking function so that it is independent of the number of relevant documents of each query.

    摘要翻译: 提供了一种用于生成用于将文档与查询的相关性排序的排序函数的方法和系统。 排名系统从包括查询,结果文档以及每个文档与其查询的相关性的训练数据中学习排名函数。 排名系统使用训练数据通过对相关文件的不正确排名加权比不相关文件的不正确排名更多地学习排名功能,以便更加重视正确排列相关文件。 排序系统还可以通过将每个查询的贡献归一化到排序函数来学习使用训练数据的排序函数,使得它独立于每个查询的相关文档的数量。

    Learning a document ranking using a loss function with a rank pair or a query parameter
    2.
    发明授权
    Learning a document ranking using a loss function with a rank pair or a query parameter 有权
    使用具有排名对或查询参数的损失函数学习文档排名

    公开(公告)号:US07593934B2

    公开(公告)日:2009-09-22

    申请号:US11460838

    申请日:2006-07-28

    IPC分类号: G06F7/00 G06F17/30 G06F15/00

    摘要: A method and system for generating a ranking function to rank the relevance of documents to a query is provided. The ranking system learns a ranking function from training data that includes queries, resultant documents, and relevance of each document to its query. The ranking system learns a ranking function using the training data by weighting incorrect rankings of relevant documents more heavily than the incorrect rankings of not relevant documents so that more emphasis is placed on correctly ranking relevant documents. The ranking system may also learn a ranking function using the training data by normalizing the contribution of each query to the ranking function so that it is independent of the number of relevant documents of each query.

    摘要翻译: 提供了一种用于生成用于将文档与查询的相关性排序的排序函数的方法和系统。 排名系统从包括查询,结果文档以及每个文档与其查询的相关性的训练数据中学习排名函数。 排名系统使用训练数据通过对相关文件的不正确排名加权比不相关文件的不正确排名更多地学习排名功能,以便更加重视正确排列相关文件。 排序系统还可以通过将每个查询的贡献归一化到排序函数来学习使用训练数据的排序函数,使得它独立于每个查询的相关文档的数量。

    DIRECTLY OPTIMIZING EVALUATION MEASURES IN LEARNING TO RANK
    3.
    发明申请
    DIRECTLY OPTIMIZING EVALUATION MEASURES IN LEARNING TO RANK 有权
    直接优化评估评估方法

    公开(公告)号:US20100082606A1

    公开(公告)日:2010-04-01

    申请号:US12237293

    申请日:2008-09-24

    IPC分类号: G06F17/30 G06F17/10

    CPC分类号: G06F17/30687 G06F17/30867

    摘要: The present invention provides methods for improving a ranking model. In one embodiment, a method includes the step of obtaining queries, documents, and document labels. The process then initializes active sets using the document labels, wherein two active sets are established for each query, a perfect active set and an imperfect active set. Then, the process optimizes an empirical loss function by the use of the first and second active set, whereby parameters of the ranking model are modified in accordance to the empirical loss function. The method then updates the active sets with additional ranking data, wherein the updates are configured to work in conjunction with the optimized loss function and modified ranking model. The recalculated active sets provide an indication for ranking the documents in a way that is more consistent with the document metadata.

    摘要翻译: 本发明提供了改进排名模型的方法。 在一个实施例中,一种方法包括获得查询,文档和文档标签的步骤。 然后,该过程使用文档标签来初始化活动集合,其中为每个查询建立两个活动集合,完美的活动集合和不完全的活动集合。 然后,该过程通过使用第一和第二活动集来优化经验损失函数,由此根据经验损失函数修改排名模型的参数。 然后,该方法用附加排名数据更新活动集合,其中更新被配置为与优化的损失函数和修改的排名模型一起工作。 重新计算的活动集提供了以与文档元数据更一致的方式对文档进行排名的指示。

    Directly optimizing evaluation measures in learning to rank
    4.
    发明授权
    Directly optimizing evaluation measures in learning to rank 有权
    直接优化学习排名评估指标

    公开(公告)号:US08478748B2

    公开(公告)日:2013-07-02

    申请号:US12237293

    申请日:2008-09-24

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30687 G06F17/30867

    摘要: The present invention provides methods for improving a ranking model. In one embodiment, a method includes the step of obtaining queries, documents, and document labels. The process then initializes active sets using the document labels, wherein two active sets are established for each query, a perfect active set and an imperfect active set. Then, the process optimizes an empirical loss function by the use of the first and second active set, whereby parameters of the ranking model are modified in accordance to the empirical loss function. The method then updates the active sets with additional ranking data, wherein the updates are configured to work in conjunction with the optimized loss function and modified ranking model. The recalculated active sets provide an indication for ranking the documents in a way that is more consistent with the document metadata.

    摘要翻译: 本发明提供了改进排名模型的方法。 在一个实施例中,一种方法包括获得查询,文档和文档标签的步骤。 然后,该过程使用文档标签来初始化活动集合,其中为每个查询建立两个活动集合,完美的活动集合和不完全的活动集合。 然后,该过程通过使用第一和第二活动集来优化经验损失函数,由此根据经验损失函数修改排名模型的参数。 然后,该方法用附加排名数据更新活动集合,其中更新被配置为与优化的损失函数和修改的排名模型一起工作。 重新计算的活动集提供了以与文档元数据更一致的方式对文档进行排名的指示。

    Ranking and accessing definitions of terms
    5.
    发明授权
    Ranking and accessing definitions of terms 失效
    排名和访问术语的定义

    公开(公告)号:US07877383B2

    公开(公告)日:2011-01-25

    申请号:US11115500

    申请日:2005-04-27

    申请人: Yunbo Cao Hang Li Jun Xu

    发明人: Yunbo Cao Hang Li Jun Xu

    IPC分类号: G06F7/00

    CPC分类号: G06F17/30654 G06F2216/03

    摘要: A method of processing information is provided. The method includes collecting text strings of definition candidates from a data source. The definition candidates are ranked based on the text strings.

    摘要翻译: 提供了处理信息的方法。 该方法包括从数据源收集定义候选的文本串。 定义候选人基于文本字符串进行排名。

    Search by document type and relevance
    6.
    发明授权
    Search by document type and relevance 失效
    按文件类型和相关性搜索

    公开(公告)号:US07644074B2

    公开(公告)日:2010-01-05

    申请号:US11275326

    申请日:2005-12-22

    申请人: Yunbo Cao Hang Li Jun Xu

    发明人: Yunbo Cao Hang Li Jun Xu

    IPC分类号: G06F17/30

    摘要: A method of finding documents. A method of finding documents comprising, ranking documents according to relevance to form a ranked relevance list, ranking documents according to type to form a ranked type list, and interpolating the ranked relevance list and the ranked type list to form a list of documents ranked by relevance and type.

    摘要翻译: 查找文档的方法。 一种查找文档的方法,包括:根据相关性对文档进行排序以形成排名相关性列表,根据类型排列文档以形成排名类型列表,以及内插排列相关性列表和排名类型列表,以形成由 相关性和类型。

    Search By Document Type And Relevance
    7.
    发明申请
    Search By Document Type And Relevance 审中-公开
    按文件类型和相关性搜索

    公开(公告)号:US20070150473A1

    公开(公告)日:2007-06-28

    申请号:US11383638

    申请日:2006-05-16

    申请人: Hang Li Yunbo Cao Jun Xu

    发明人: Hang Li Yunbo Cao Jun Xu

    IPC分类号: G06F7/00

    CPC分类号: G06F16/951

    摘要: A method of finding documents. A method of finding documents comprising, ranking documents according to relevance to form a ranked relevance list, ranking documents according to type to form a ranked type list, and combining the ranked relevance list and the ranked type list to form a list of documents ranked by relevance and type.

    摘要翻译: 查找文档的方法。 一种查找文档的方法,包括:根据相关性对文档进行排序以形成排名相关性列表,根据类型排列文档以形成排名类型列表,以及组合排名相关性列表和排名类型列表,以形成由 相关性和类型。

    Ranking and accessing definitions of terms
    8.
    发明申请
    Ranking and accessing definitions of terms 失效
    排名和访问术语的定义

    公开(公告)号:US20060248049A1

    公开(公告)日:2006-11-02

    申请号:US11115500

    申请日:2005-04-27

    申请人: Yunbo Cao Hang Li Jun Xu

    发明人: Yunbo Cao Hang Li Jun Xu

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30654 G06F2216/03

    摘要: A method of processing information is provided. The method includes collecting text strings of definition candidates from a data source. The definition candidates are ranked based on the text strings.

    摘要翻译: 提供了处理信息的方法。 该方法包括从数据源收集定义候选的文本串。 定义候选人基于文本字符串进行排名。

    Search By Document Type
    9.
    发明申请
    Search By Document Type 失效
    按文档类型搜索

    公开(公告)号:US20070150472A1

    公开(公告)日:2007-06-28

    申请号:US11275326

    申请日:2005-12-22

    申请人: Yunbo Cao Hang Li Jun Xu

    发明人: Yunbo Cao Hang Li Jun Xu

    IPC分类号: G06F7/00

    摘要: A method of finding documents. A method of finding documents comprising, ranking documents according to relevance to form a ranked relevance list, ranking documents according to type to form a ranked type list, and interpolating the ranked relevance list and the ranked type list to form a list of documents ranked by relevance and type.

    摘要翻译: 查找文档的方法。 一种查找文档的方法,包括:根据相关性对文档进行排序以形成排名相关性列表,根据类型排列文档以形成排名类型列表,以及内插排列相关性列表和排名类型列表,以形成由 相关性和类型。

    Query expansion for web search
    10.
    发明授权
    Query expansion for web search 有权
    网页搜索的查询扩展

    公开(公告)号:US08898156B2

    公开(公告)日:2014-11-25

    申请号:US13040192

    申请日:2011-03-03

    申请人: Jun Xu Hang Li

    发明人: Jun Xu Hang Li

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30864 G06F17/30672

    摘要: Systems, methods, and devices are described for retrieving query results based at least in part on a query and one or more similar queries. Upon receiving a query, one or more similar queries may be identified and/or calculated. In one embodiment, the similar queries may be determined based at least in part on click-through data corresponding to previously submitted queries. Information associated with the query and each of the similar queries may be retrieved, ranked, and or combined. The combined query results may then be re-ranked based at least in part on a responsiveness and/or relevance to the previously submitted query. The re-ranked query results may then be output to a user that submitted the original query.

    摘要翻译: 描述了至少部分地基于查询和一个或多个类似查询来检索查询结果的系统,方法和设备。 在接收到查询时,可以识别和/或计算一个或多个类似的查询。 在一个实施例中,可以至少部分地基于对应于先前提交的查询的点击数据来确定类似的查询。 与查询相关联的信息和每个相似查询可以被检索,排序和/或组合。 组合的查询结果可以至少部分地基于对先前提交的查询的响应性和/或相关性来重新排序。 然后可以将重新排列的查询结果输出给提交原始查询的用户。