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    • 84. 发明授权
    • Software error report analysis
    • 软件错误报告分析
    • US07890814B2
    • 2011-02-15
    • US11823213
    • 2007-06-27
    • Dongmei ZhangYingnong DangXiaohui HouSong HuangJian Wang
    • Dongmei ZhangYingnong DangXiaohui HouSong HuangJian Wang
    • G06F11/00
    • G06F11/366
    • 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).
    • 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。
    • 86. 发明授权
    • Efficient data infrastructure for high dimensional data analysis
    • 高维数据基础架构,用于高维数据分析
    • US07870114B2
    • 2011-01-11
    • US11818879
    • 2007-06-15
    • Haidong ZhangGuowei LiuYantao LiBing SunJian Wang
    • Haidong ZhangGuowei LiuYantao LiBing SunJian Wang
    • G06F17/30
    • G06F17/30592
    • Described is a technology by which high dimensional source data corresponding to rows of records with identifiers, and columns comprising dimensions of data values, are processed into a file model for efficient access. An inverted index corresponding to any dimension is built by mapping data from raw dimension values to mapped values based on mapping entries in a dimension table. The record identifiers are arranged into subgroups based on their mapped value; a count and/or an offset may be maintained for locating each of the subgroups. The raw values for a dimension are maintained within a raw value file. For sparse data, the raw value file may be compressed, e.g., by excluding nulls and associating a record identifier with each non-null. A data manager provides access to data in the data files, such as by offering various functions, using caching for efficiency.
    • 描述了一种技术,通过该技术将对应于具有标识符的记录行的高维源数据和包括数据值的维的列处理成用于有效访问的文件模型。 通过根据维度表中的映射条目将数据从原始维度值映射到映射值,构建对应于任何维度的反向索引。 记录标识符根据其映射值排列成子组; 可以维持计数和/或偏移以定位每个子组​​。 维度的原始值保持在原始值文件中。 对于稀疏数据,可以例如通过排除空值并将记录标识符与每个非空值相关联来压缩原始值文件。 数据管理器提供对数据文件中的数据的访问,例如通过提供各种功能,使用缓存来提高效率。
    • 87. 发明授权
    • Abbreviation expansion based on learned weights
    • 基于学习权重的缩写扩展
    • US07848918B2
    • 2010-12-07
    • US11538770
    • 2006-10-04
    • Hua LiSong HuangZheng ChenJian Wang
    • Hua LiSong HuangZheng ChenJian Wang
    • G06F17/27G06F17/21G10L21/00
    • G06F17/28
    • A method and system for identifying expansions of abbreviations using learned weights is provided. An abbreviation system generates features for various expansions of an abbreviation and generates a score indicating the likelihood that an expansion is a correct expansion of the abbreviation. A expansion with the same number of words as letters in the abbreviation is more likely in general to be a correct expansion than an expansion with more or fewer words. The abbreviation system calculates a score based on a weighted combination of the features. The abbreviation system learns the weights for the features from training data of abbreviations, candidate expansions, and scores for the candidate expansions.
    • 提供了一种用于使用学习的权重来识别缩写的扩展的方法和系统。 缩写系统产生缩写的各种扩展的特征,并生成表示扩展是缩写的正确扩展的可能性的分数。 与缩写中的字母相同数量的单词的扩展通常可能是具有更多或更少单词的扩展的正确扩展。 缩写系统基于特征的加权组合来计算得分。 缩写系统从候选扩展的缩写,候选扩展和分数的训练数据中学习特征的权重。
    • 88. 发明授权
    • Real-time operating optimized method of multi-input and multi-output continuous manufacturing procedure
    • 多输入多输出连续制造程序的实时操作优化方法
    • US07848831B2
    • 2010-12-07
    • US11988889
    • 2005-12-27
    • Jian Wang
    • Jian Wang
    • G05B13/02G06F7/60G06F17/10G06F15/18G06E1/00G06E3/00G06G7/00
    • G05B11/42G05B2219/31265G05B2219/32015
    • A real-time operating optimized method of multi-input and multi-output continuous manufacture procedure includes steps as follows: first, using plurality of pivotal operation conditions in the manufacture procedure as optimized variables, and using the technical target associating with the pivotal operation conditions as the objective function, then, calculating on line the grades vector between pivotal operation conditions and the technical target at current time according to historical data of pivotal operation conditions and the technical target, using correlation integral method or other methods, at last, using this grades vector to define the adjustment direction of the operation conditions. When the grades vector is positive or negative, the pivotal operation conditions should be adjusted in order to change the grades vector to zero.
    • 多输入多输出连续制造程序的实时操作优化方法包括以下步骤:首先,将制造过程中的多个关键操作条件作为优化变量,并使用与关键操作条件相关的技术目标 作为目标函数,然后根据关键运行条件和技术目标的历史数据,使用相关积分法或其他方法,在关键运行条件和当前技术目标之间的等级矢量线上计算,最后使用此 等级向量来定义操作条件的调整方向。 当等级矢量为正或负时,应调整关键操作条件,以将等级矢量改为零。
    • 89. 发明授权
    • Scalable probabilistic latent semantic analysis
    • 可扩展概率潜在语义分析
    • US07844449B2
    • 2010-11-30
    • US11392763
    • 2006-03-30
    • Chenxi LinJie HanGuirong XueHua-Jun ZengBenyu ZhangZheng ChenJian Wang
    • Chenxi LinJie HanGuirong XueHua-Jun ZengBenyu ZhangZheng ChenJian Wang
    • G06F17/27
    • G06F17/2785
    • A scalable two-pass scalable probabilistic latent semantic analysis (PLSA) methodology is disclosed that may perform more efficiently, and in some cases more accurately, than traditional PLSA, especially where large and/or sparse data sets are provided for analysis. The improved methodology can greatly reduce the storage and/or computational costs of training a PLSA model. In the first pass of the two-pass methodology, objects are clustered into groups, and PLSA is performed on the groups instead of the original individual objects. In the second pass, the conditional probability of a latent class, given an object, is obtained. This may be done by extending the training results of the first pass. During the second pass, the most likely latent classes for each object are identified.
    • 公开了一种可扩展的双向可伸缩概率潜在语义分析(PLSA)方法,其可以比传统的PLSA更有效地执行,在某些情况下可以更准确地执行,特别是在提供大型和/或稀疏数据集用于分析的情况下。 改进的方法可以大大降低培训PLSA模型的存储和/或计算成本。 在双路方法的第一遍中,对象被聚集成组,并且PLSA在组而不是原始的单个对象上执行。 在第二遍中,获得给定对象的潜在类的条件概率。 这可以通过扩展第一遍的训练结果来完成。 在第二遍期间,识别每个对象最可能的潜在类。
    • 90. 发明授权
    • Efficient retrieval algorithm by query term discrimination
    • 通过查询词辨别的有效检索算法
    • US07822752B2
    • 2010-10-26
    • US11804627
    • 2007-05-18
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • Chenxi LinLei JiHuajun ZengBenyu ZhangZheng ChenJian Wang
    • G06F7/00G06F17/30
    • G06F17/30675
    • Described is an efficient retrieval mechanism that quickly locates documents (e.g., corresponding to online advertisements) based on query term discrimination. A topmost subset (e.g., two) of search terms is selected according to their ranked importance, e.g., as ranked by inverted document frequency. The topmost terms are then used to narrow the number of rows of an inverted query index that are searched to find document identifiers and associated scores, such as computed offline by a BM25 algorithm. For example, for each document identifier of each important term, a fast search within each of the narrowed subset of rows (that also contain that document identifier) may be performed by comparing document identifiers to jump a pointer within each other row, followed by a binary search to locate a particular document. The scores of the set of particular documents may then be used to rank their relative importance for returning as results.
    • 描述了一种有效的检索机制,其基于查询词辨别快速定位文档(例如,对应于在线广告)。 根据其排序的重要性来选择搜索项的最顶层子集(例如,两个),例如按照倒排的文档频率排序。 然后使用最上面的术语来缩小被搜索以查找文档标识符和相关分数的反向查询索引的行数,例如通过BM25算法离线计算。 例如,对于每个重要术语的每个文档标识符,可以通过比较文档标识符来跳过每个其他行中的指针,然后是一个指针,来执行每个狭窄的行子集(也包含该文档标识符)的快速搜索 二进制搜索查找特定文档。 然后可以使用该组特定文件的分数来排列其作为结果返回的相对重要性。