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31. 发明申请

US20120278658A1 Analyzing Software Performance Issues 有权
标题翻译：分析软件性能问题
公开(公告)号：US20120278658A1
公开(公告)日：2012-11-01
申请号：US13095269
申请日：2011-04-27
申请人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang , Bin Zhao , Feng Liang , Chao Bian , Xiangpeng Zhao , Cong Chen , Hang Li , Prashant Ratanchandani
发明人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang , Bin Zhao , Feng Liang , Chao Bian , Xiangpeng Zhao , Cong Chen , Hang Li , Prashant Ratanchandani
IPC分类号： G06F11/36
CPC分类号： G06F11/3636
摘要： Execution traces are collected from multiple execution instances that exhibit performance issues such as slow execution. Call stacks are extracted from the execution traces, and the call stacks are mined to identify frequently occurring function call patterns. The call patterns are then clustered, and used to identify groups of execution instances whose performance issues may be caused by common problematic program execution patterns.
摘要翻译：从执行缓慢执行的性能问题的多个执行实例中收集执行跟踪。从执行跟踪中提取调用堆栈，并且调用堆栈被挖掘以识别经常出现的函数调用模式。呼叫模式然后被聚集，并用于识别其性能问题可能由常见的有问题的程序执行模式引起的执行实例组。

32. 发明授权

US09348852B2 Frequent pattern mining 有权
标题翻译：频繁模式挖掘
公开(公告)号：US09348852B2
公开(公告)日：2016-05-24
申请号：US13095415
申请日：2011-04-27
申请人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang
发明人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang
IPC分类号： G06F17/30
CPC分类号： G06F17/30539 , G06F17/30306 , H04L67/10
摘要： A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.
摘要翻译：用于频繁模式挖掘的系统使用两层处理：多个计算节点和每个计算节点内的多个处理器。在每个计算节点内，将要执行频繁模式挖掘的数据集存储在共享存储器中，由每个处理器并发访问。搜索空间在计算节点之间划分，并在每个计算节点的处理器之间进行子分区。如果处理器完成其子分区，则它请求另一个子分区。可以动态执行分区和子分区，并实时调整。

33. 发明申请

US20120278346A1 Frequent Pattern Mining 有权
标题翻译：频繁模式挖掘
公开(公告)号：US20120278346A1
公开(公告)日：2012-11-01
申请号：US13095415
申请日：2011-04-27
申请人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang
发明人： Shi Han , Yingnong Dang , Song Ge , Dongmei Zhang
IPC分类号： G06F17/30
CPC分类号： G06F17/30539 , G06F17/30306 , H04L67/10
摘要： A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.
摘要翻译：用于频繁模式挖掘的系统使用两层处理：多个计算节点和每个计算节点内的多个处理器。在每个计算节点内，将要执行频繁模式挖掘的数据集存储在共享存储器中，由每个处理器并发访问。搜索空间在计算节点之间划分，并在每个计算节点的处理器之间进行子分区。如果处理器完成其子分区，则它请求另一个子分区。可以动态执行分区和子分区，并实时调整。

34. 发明申请

US20120143795A1 CROSS-TRACE SCALABLE ISSUE DETECTION AND CLUSTERING 有权
标题翻译：跨轨迹可扩展问题检测和聚类
公开(公告)号：US20120143795A1
公开(公告)日：2012-06-07
申请号：US12960015
申请日：2010-12-03
申请人： Shi Han , Yingnong Dang , Shuo-Hsien (Stephen) Hsiao , Dongmei Zhang
发明人： Shi Han , Yingnong Dang , Shuo-Hsien (Stephen) Hsiao , Dongmei Zhang
IPC分类号： G06F11/07 , G06F15/18
CPC分类号： G06F11/079 , G06F11/3409 , G06F11/3447 , H04L41/0636 , H04L41/16
摘要： Techniques and systems for cross-trace scalable issue detection and clustering that scale-up trace analysis for issue detection and root-cause clustering using a machine learning based approach are described herein. These techniques enable a scalable performance analysis framework for computing devices addressing issue detection, which is designed as a multiple scale feature for learning based issue detection, and root cause clustering. In various embodiments the techniques employ a cross-trace similarity model, which is defined to hierarchically cluster problems detected in the learning based issue detection via butterflies of trigram stacks. The performance analysis framework is scalable to manage millions of traces, which include high problem complexity.
摘要翻译：本文描述了用于交叉跟踪可扩展问题检测和聚类的技术和系统，其中使用基于机器学习的方法对用于问题检测和根本原因聚类进行放大跟踪分析。这些技术使得可扩展的性能分析框架用于处理问题检测的计算设备，其被设计为用于基于学习的问题检测的多尺度特征以及根本原因聚类。在各种实施例中，该技术采用交叉跟踪相似性模型，其被定义为通过三元组栈的蝴蝶在基于学习的问题检测中分层检测集群问题。性能分析框架是可扩展的，以管理数百万条跟踪，其中包括高问题复杂性。

35. 发明授权

US09147271B2 Graphical representation of aggregated data 有权
标题翻译：聚合数据的图形表示
公开(公告)号：US09147271B2
公开(公告)日：2015-09-29
申请号：US11820636
申请日：2007-06-20
申请人： Yingnong Dang , Dongmei Zhang , Min Wang , Xiaohui Hou , Jian Wang
发明人： Yingnong Dang , Dongmei Zhang , Min Wang , Xiaohui Hou , Jian Wang
IPC分类号： G06F3/048 , G06T11/20 , G06F21/57
CPC分类号： G06T11/206 , G06F21/577
摘要： A method for enabling graphical representation of aggregated data is provided. The method includes accessing aggregated data retrieved from a plurality of on-line sources and receiving selection of a portion of the data through a graphical user interface. The method further includes identifying attributes associated with the portion of the data and generating a graphical representation of the portion of the data.
摘要翻译：提供了一种用于实现聚合数据的图形表示的方法。该方法包括访问从多个在线源检索的聚合数据，并通过图形用户界面接收对部分数据的选择。所述方法还包括识别与所述数据的所述部分相关联的属性并且生成所述数据的所述部分的图形表示。

36. 发明授权

US08041120B2 Unified digital ink recognition 有权
标题翻译：统一数字墨水识别
公开(公告)号：US08041120B2
公开(公告)日：2011-10-18
申请号：US11821858
申请日：2007-06-26
申请人： Dongmei Zhang , Xiaohui Hou , Yingjun Qiu , Jian Wang
发明人： Dongmei Zhang , Xiaohui Hou , Yingjun Qiu , Jian Wang
IPC分类号： G06K9/46 , G06K9/66
CPC分类号： G06K9/00422
摘要： Described is a unified digital ink recognizer that recognizes various different types of digital ink data, such as handwritten character data and custom data, e.g., sketched shapes, handwritten gestures, and/or drawn pictures, without further participation by a user such as recognition mode selection or parameter input. For a custom item, the output may be a Unicode value from a private use area of Unicode. Building the unified digital ink recognizer may include defining the data set to be recognized, extracting features of training samples corresponding to the dataset items to build a recognizer model, evaluating the recognizer model using testing data, and modifying the recognizer model using tuning data. The extracted features may be processed into feature data for a multi-dimensional nearest neighbor recognizer approach; the extracted features for the samples of each class is calculated and combined into the feature set for this class in the resulting recognizer model.
摘要翻译：描述了一种统一的数字墨水识别器，其识别各种不同类型的数字墨水数据，例如手写字符数据和自定义数据，例如草图形状，手写手势和/或绘制的图像，而不需要诸如识别模式的用户的进一步参与选择或参数输入。对于自定义项目，输出可能是Unicode的私有使用区域的Unicode值。构建统一数字墨水识别器可以包括定义要识别的数据集，提取与数据集项目相对应的训练样本的特征以构建识别器模型，使用测试数据评估识别器模型，以及使用调谐数据修改识别器模型。提取的特征可以被处理成用于多维最近邻识别器方法的特征数据; 计算每个类的样本的提取特征，并将其组合到生成的识别器模型中的该类的特征集中。

37. 发明授权

US07890814B2 Software error report analysis 有权
标题翻译：软件错误报告分析
公开(公告)号：US07890814B2
公开(公告)日：2011-02-15
申请号：US11823213
申请日：2007-06-27
申请人： Dongmei Zhang , Yingnong Dang , Xiaohui Hou , Song Huang , Jian Wang
发明人： Dongmei Zhang , Yingnong Dang , Xiaohui Hou , Song Huang , Jian Wang
IPC分类号： G06F11/00
CPC分类号： G06F11/366
摘要： Described herein is technology for, among other things, accessing error report information. It involves various techniques and tools for analyzing and interrelating failure data contained in error reports and thereby facilitating developers to more easily and quickly solve programming bugs. Numerous parameters may also be specified for selecting and searching error reports. Several reliability metrics are provided to better track software reliability situations. The reliability metrics facilitate the tracking of the overall situation of failures that happen in the real word by providing metrics based on error reports (e.g., failure occurrence trends, failure distributions across different languages).
摘要翻译：这里描述的是用于访问错误报告信息的技术。它涉及用于分析和相互关联错误报告中包含的故障数据的各种技术和工具，从而方便开发人员更轻松，快速地解决编程错误。还可以指定许多参数来选择和搜索错误报告。提供了几个可靠性指标来更好地跟踪软件可靠性情况。可靠性指标通过提供基于错误报告（例如，故障发生趋势，跨不同语言的故障分布）的度量来促进跟踪真实单词中发生的故障的总体情况。

38. 发明申请

US20100191793A1 Symbolic Computation Using Tree-Structured Mathematical Expressions 审中-公开
标题翻译：使用树结构数学表达式的符号计算
公开(公告)号：US20100191793A1
公开(公告)日：2010-07-29
申请号：US12360853
申请日：2009-01-28
申请人： Xu Yang , Xiaolin Quan , Dongmei Zhang , Gong Cheng , Jian Wang , Hao Wei
发明人： Xu Yang , Xiaolin Quan , Dongmei Zhang , Gong Cheng , Jian Wang , Hao Wei
IPC分类号： G06F7/38 , G06F17/10
CPC分类号： G06F17/10 , G06F7/38
摘要： A method for performing symbolic computations on a mathematical expression. The mathematical expression may be converted to a tree structure having one or more parent nodes and one or more child nodes. Each parent node may be a mathematical operation. Each child node may be a mathematical expression on which the mathematical operation is performed in a specified order. Each child node may be in a hierarchical relationship to one of the parent nodes. The parent nodes, the child nodes or both may be manipulated to perform a first symbolic computation on the mathematical expression.
摘要翻译：一种用于对数学表达式执行符号计算的方法。数学表达式可以转换为具有一个或多个父节点和一个或多个子节点的树结构。每个父节点可以是数学运算。每个子节点可以是以指定顺序执行数学运算的数学表达式。每个子节点可以与父节点中的一个分层关系。可以操纵父节点，子节点或两者以对数学表达式执行第一符号计算。

39. 发明申请

US20100169605A1 ARBITRARY PRECISION FLOATING NUMBER PROCESSING 有权
标题翻译：仲裁精度浮数代码处理
公开(公告)号：US20100169605A1
公开(公告)日：2010-07-01
申请号：US12346061
申请日：2008-12-30
申请人： Xu Yang , Hao Wei , Gong Cheng , ZhangZhang Song , Dongmei Zhang , Jian Wang
发明人： Xu Yang , Hao Wei , Gong Cheng , ZhangZhang Song , Dongmei Zhang , Jian Wang
IPC分类号： G06F12/02 , G06F7/38
CPC分类号： G06F7/483 , G06F7/49957
摘要： Techniques for providing arbitrary precision floating number (APFN) processing are disclosed. In some aspects, an APFN store may be used to store a large number (i.e., an APFN) having many significant digits, which in turn may enable a high degree of precision in mathematical operations. An APFN module may be used to create and define the APFN store. The APFN module may enable a user to define a precision (significant digits) for the large number that corresponds to the size of an array of bytes in the APFN store that are allocated for storing the large number. In further aspects, the APFN store may be used to store additional intermediary data and a resultant.
摘要翻译：公开了提供任意精度浮动数（APFN）处理的技术。在一些方面，可以使用APFN存储来存储具有许多有效数字的大量（即，APFN），这又可以使数学运算中的高度精度。可以使用APFN模块来创建和定义APFN存储。 APFN模块可以使用户能够为与分配用于存储大数量的APFN存储中的字节数组的大小相对应的大数量定义精确度（有效数字）。在另外的方面，APFN存储可以用于存储附加的中间数据和结果。

40. 发明申请

US20080243503A1 MINIMUM DIVERGENCE BASED DISCRIMINATIVE TRAINING FOR PATTERN RECOGNITION 审中-公开
标题翻译：最小的基于分歧的歧视识别训练
公开(公告)号：US20080243503A1
公开(公告)日：2008-10-02
申请号：US11694375
申请日：2007-03-30
申请人： Frank Kao-Ping Soong , Peng Liu , Jian-Iai Zhou , Dongmei Zhang
发明人： Frank Kao-Ping Soong , Peng Liu , Jian-Iai Zhou , Dongmei Zhang
IPC分类号： G10L15/06
CPC分类号： G10L15/063
摘要： A method of providing discriminative training of a speech recognition unit is discussed. The method includes receiving an acoustic indication of an utterance having a hypothesis space and comparing the hypothesis space against a reference. The method measures the Kullback-Leibler Divergence (KLD) between the reference and the hypothesis space to adjust the reference and stores the adjusted reference on a tangible storage medium.
摘要翻译：讨论了提供语音识别单元的辨别性训练的方法。该方法包括接收具有假设空间的话语的声学指示，并将假设空间与参考值进行比较。该方法测量参考和假设空间之间的Kullback-Leibler发散（KLD）以调整参考，并将调整的参考存储在有形存储介质上。

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