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183 条记录 (耗时 0.036 秒)

    System and method of measuring real-time current
    33.
    发明授权
    System and method of measuring real-time current 有权
    测量实时电流的系统和方法

    公开(公告)号：US09122472B2

    公开(公告)日：2015-09-01

    申请号：US13787080

    申请日：2013-03-06

    申请人： Shiguo Luo ,  Ralph H. Johnson, III ,  James L. Petivan, III ,  Hang Li

    发明人： Shiguo Luo ,  Ralph H. Johnson, III ,  James L. Petivan, III ,  Hang Li

    IPC分类号： G01R19/25 ,  G06F1/28 ,  G01R31/40 ,  G01R19/00

    CPC分类号： G01R19/2513 ,  G01R19/003 ,  G01R19/25 ,  G01R31/40 ,  G01R35/005 ,  G06F1/28

    摘要： A system and method of measuring real-time current is disclosed. The method includes calibrating a voltage measurement device. Calibrating includes measuring a real-time voltage difference between a first measurement node located proximate a first connector on a motherboard and a second measurement node located proximate a second connector on a power supply unit (PSU), the first and the second connectors coupled to provide power to the motherboard. Calibrating further includes averaging the real-time voltage difference for a plurality of measurements; computing a resistance of the coupling based at least on a long-duration averaged current from the PSU and the averaged real-time voltage difference, the resistance varying over time; and reporting the resistance of the coupling to the voltage measurement device. The method also includes measuring a real-time current of the PSU at the voltage measurement device based at least on the resistance of the coupling and the real-time voltage difference.

    摘要翻译： 公开了一种测量实时电流的系统和方法。 该方法包括校准电压测量装置。 校准包括测量位于母板上的第一连接器附近的第一测量节点与位于电源单元（PSU）上的第二连接器附近的第二测量节点之间的实时电压差，第一和第二连接器被耦合以提供 电源到主板。 校准还包括对多个测量的实时电压差进行平均化; 至少基于来自PSU的长持续时间平均电流和平均实时电压差计算耦合电阻，电阻随时间变化; 并报告耦合到电压测量装置的电阻。 该方法还包括至少基于耦合的电阻和实时电压差来测量电压测量装置处的PSU的实时电流。

    Query expansion for web search
    34.
    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。

    Search results ranking using editing distance and document information
    35.
    发明授权
    Search results ranking using editing distance and document information 有权
    使用编辑距离和文档信息搜索结果排名

    公开(公告)号：US08812493B2

    公开(公告)日：2014-08-19

    申请号：US12101951

    申请日：2008-04-11

    申请人： Vladimir Tankovich ,  Hang Li ,  Dmitriy Meyerzon ,  Jun Xu

    发明人： Vladimir Tankovich ,  Hang Li ,  Dmitriy Meyerzon ,  Jun Xu

    IPC分类号： G06F7/00

    CPC分类号： G06F17/2211 ,  G06F17/30864

    摘要： Architecture for extracting document information from documents received as search results based on a query string, and computing an edit distance between the data string and the query string. The edit distance is employed in determining relevance of the document as part of result ranking by detecting near-matches of a whole query or part of the query. The edit distance evaluates how close the query string is to a given data stream that includes document information such as TAUC (title, anchor text, URL, clicks) information, etc. The architecture includes the index-time splitting of compound terms in the URL to allow the more effective discovery of query terms. Additionally, index-time filtering of anchor text is utilized to find the top N anchors of one or more of the document results. The TAUC information can be input to a neural network (e.g., 2-layer) to improve relevance metrics for ranking the search results.

    摘要翻译： 用于基于查询字符串从作为搜索结果接收的文档提取文档信息的结构，以及计算数据串和查询字符串之间的编辑距离。 编辑距离用于通过检测整个查询或部分查询的近似匹配来确定文档作为结果排名的一部分的相关性。 编辑距离评估查询字符串与包含诸如TAUC（标题，锚文本，URL，点击）信息等文档信息的给定数据流的距离。该体系结构包括索引时间分割URL中的复合术语 以便更有效地发现查询条款。 另外，使用锚文本的索引时间过滤来查找一个或多个文档结果的前N个锚点。 可以将TAUC信息输入到神经网络（例如，2层），以改进用于对搜索结果排序的相关性度量。

    Predicting users' attributes based on users' behaviors
    36.
    发明授权
    Predicting users' attributes based on users' behaviors 有权
    根据用户的行为预测用户的属性

    公开(公告)号：US08756184B2

    公开(公告)日：2014-06-17

    申请号：US12957649

    申请日：2010-12-01

    申请人： Hang Li ,  Hua Zheng ,  Ting-hao Yang ,  Richard W. Tom ,  Yupeng Liao ,  Qi Zhang

    发明人： Hang Li ,  Hua Zheng ,  Ting-hao Yang ,  Richard W. Tom ,  Yupeng Liao ,  Qi Zhang

    IPC分类号： G06F15/18 ,  G06N3/08 ,  G06N3/04 ,  G06N7/00

    CPC分类号： G06N3/0436 ,  G06F15/18 ,  G06N3/08 ,  G06N7/005

    摘要： A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to predict and utilize a user's attributes. A sample user behavior and a sample user attribute are collected. A model is trained based on the sample user behavior and sample user attribute. Using the model, a probability of a predicted user attribute based on the sample user behavior is predicted. Using the model and the probability, the predicted user attribute is fuzzily determined based on a real user behavior. The predicted user attribute is used to improve a user's experience.

    摘要翻译： 方法，装置，系统，制品和计算机可读存储介质提供预测和利用用户属性的能力。 收集示例用户行为和示例用户属性。 根据样本用户行为和样本用户属性对模型进行培训。 使用该模型，预测基于样本用户行为的预测用户属性的概率。 使用模型和概率，基于真实用户行为模糊地确定预测用户属性。 预测的用户属性用于改善用户体验。

    Learning similarity function for rare queries
    37.
    发明授权
    Learning similarity function for rare queries 有权
    学习罕见查询的相似度函数

    公开(公告)号：US08612367B2

    公开(公告)日：2013-12-17

    申请号：US13021446

    申请日：2011-02-04

    申请人： Jingfang Xu ,  Gu Xu ,  Hang Li

    发明人： Jingfang Xu ,  Gu Xu ,  Hang Li

    IPC分类号： G06F15/18

    CPC分类号： G06N99/005 ,  H04L9/3236

    摘要： Techniques are described for determining queries that are similar to rare queries. An n-gram space is defined to represent queries and a similarity function is defined to measure the similarities between queries. The similarity function is learned by leveraging training data derived from user behavior data and formalized as an optimization problem using a metric learning approach. Furthermore, the similarity function can be defined in the n-gram space, which is equivalent to a cosine similarity in a transformed n-gram space. Locality sensitive hashing can be exploited for efficient retrieval of similar queries from a large query repository. This technique can be used to enhance the accuracy of query similarity calculation for rare queries, facilitate the retrieval of similar queries and significantly improve search relevance.

    摘要翻译： 描述了用于确定与罕见查询类似的查询的技术。 定义n-gram空间来表示查询，并且定义相似度函数来测量查询之间的相似性。 通过利用从用户行为数据导出的训练数据，并使用度量学习方法将其形式化为优化问题，来学习相似度函数。 此外，可以在n-gram空间中定义相似度函数，这相当于在变换的n-gram空间中的余弦相似度。 可以利用局部敏感散列来高效地检索大型查询库中的类似查询。 这种技术可以用于提高罕见查询的查询相似度计算的准确性，便于检索类似的查询，并显着提高搜索的相关性。

    Regularized latent semantic indexing for topic modeling
    38.
    发明授权
    Regularized latent semantic indexing for topic modeling 有权
    主题建模的正则化潜在语义索引

    公开(公告)号：US08533195B2

    公开(公告)日：2013-09-10

    申请号：US13169808

    申请日：2011-06-27

    申请人： Jun Xu ,  Hang Li ,  Nicholas Craswell

    发明人： Jun Xu ,  Hang Li ,  Nicholas Craswell

    IPC分类号： G06F7/00 ,  G06F17/30 ,  G06F17/16 ,  G06F17/11 ,  G06F11/34

    CPC分类号： G06F17/16 ,  G06F11/3447 ,  G06F17/11 ,  G06F17/30705 ,  G06F2212/454 ,  G06K9/00979 ,  G06K9/6249

    摘要： Electronic documents are retrieved from a database and/or from a network of servers. The documents are topic modeled in accordance with a Regularized Latent Semantic Indexing approach. The Regularized Latent Semantic Indexing approach may allow an equation involving an approximation of a term-document matrix to be solved in parallel by multiple calculating units. The equation may include terms that are regularized via either l1 norm and/or via l2 norm. The Regularized Latent Semantic Indexing approach may be applied to a set, or a fixed number, of documents such that the set of documents is topic modeled. Alternatively, the Regularized Latent Semantic Indexing approach may be applied to a variable number of documents such that, over time, the variable of number of documents is topic modeled.

    摘要翻译： 从数据库和/或从服务器网络检索电子文档。 这些文件是根据正则潜在语义索引方法建模的主题。 正则潜在语义索引方法可以允许涉及术语文档矩阵的近似的等式由多个计算单元并行求解。 方程式可以包括通过l1范数和/或通过l2范数规则化的项。 正则潜在语义索引方法可以应用于一组或固定数量的文档，使得该组文档被主题建模。 或者，正则潜在语义索引方法可以应用于可变数量的文档，使得随着时间的推移，文档数量的变量被主题建模。

    Directly optimizing evaluation measures in learning to rank
    39.
    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

    申请人： Jun Xu ,  Tie-Yan Liu ,  Hang Li

    发明人： Jun Xu ,  Tie-Yan Liu ,  Hang Li

    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。