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71. 发明授权

US08160982B2 Method for detecting people of interest from information sources 有权
标题翻译：从信息来源检测感兴趣的人的方法
公开(公告)号：US08160982B2
公开(公告)日：2012-04-17
申请号：US12319167
申请日：2008-12-31
申请人： Zhongfei Zhang , John J. Salerno
发明人： Zhongfei Zhang , John J. Salerno
IPC分类号： G06E1/00 , G06F1/00
CPC分类号： G06Q40/02 , G06Q20/10 , G06Q20/4016 , G06Q30/02 , G06Q40/10
摘要： A method for detecting people of interest from information sources. Method performs automatic community model generation based on uni-parity data. Correlation analysis is employed to identify links within the community. Method may be particularized for solving specific problems, for example, such as determining the activities between individuals within a money laundering ring.
摘要翻译：一种从信息来源检测感兴趣的人的方法。方法基于单一奇偶校验数据执行自动社区模型生成。使用相关分析来识别社区内的链接。方法可以被特别地用于解决具体问题，例如确定洗钱环内的个体之间的活动。

72. 发明授权

US08156056B2 Method and system of classifying, ranking and relating information based on weights of network links 有权
标题翻译：基于网络链路权重对信息进行分类，排序和相关的方法和系统
公开(公告)号：US08156056B2
公开(公告)日：2012-04-10
申请号：US12076917
申请日：2008-03-25
申请人： Fernando Luege Mateos
发明人： Fernando Luege Mateos
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00
CPC分类号： G06F17/30702 , G06F17/3069
摘要： What is disclosed is an automatic method of classification, qualification and relation of information that is based on a network built starting from the semantic, numeric, conceptual, etc. relationships between elements of different sets that are structurally alike. Through the topological properties of the network, we generate a vector of relations for each element that allows us to analyze the similarity among them, improve and facilitate the clustering processes, carry out personalized dynamic ranking, analyze conduct patterns as well as maintain the auto evolving dynamic of the network through the interaction and feedback of its elements, among other characteristics.
摘要翻译：所揭示的是一种基于从结构上相似的不同集合的元素之间的语义，数字，概念等关系开始构建的网络的分类，限定和信息的自动方法。通过网络的拓扑属性，我们为每个元素生成一个关系的向量，使我们能够分析它们之间的相似性，改进和促进聚类过程，实现个性化的动态排名，分析行为模式以及维护自动发展动态的网络通过其元素的交互和反馈等特点。

73. 发明授权

US08121962B2 Automated entity identification for efficient profiling in an event probability prediction system 有权
标题翻译：自动实体识别用于事件概率预测系统中的高效分析
公开(公告)号：US08121962B2
公开(公告)日：2012-02-21
申请号：US12110261
申请日：2008-04-25
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06F15/18 , G06E1/00 , G06E3/00 , G06G7/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史简档，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

74. 发明授权

US08112373B2 Nerve equivalent circuit, synapse equivalent circuit and nerve cell body equivalent circuit 有权
标题翻译：神经等效电路，突触等效电路和神经细胞体等效电路
公开(公告)号：US08112373B2
公开(公告)日：2012-02-07
申请号：US12281812
申请日：2007-03-05
申请人： Xiaolin Zhang , Yoshinori Maeda
发明人： Xiaolin Zhang , Yoshinori Maeda
IPC分类号： G06E1/00 , G06G7/58
CPC分类号： G06N3/0635
摘要： A nerve equivalent circuit, a synapse equivalent circuit and a cell body equivalent circuit are provided whereby electrical characteristics in accordance with the physiological functions and physical structures of nerve cells are reproduced. A nerve equivalent circuit simulating the electrical characteristics of nerve cells wherein an input signal fin(t) and an output signal fout(t) satisfies the relationship represented by [Numerical formula 11], wherein kP, kI and TI are each a definite constant number, N represents the total number of synapses, M represents the total number of the kinds of the first transmitters carried by the synapses, and L represents the total number of the kinds of the second transmitters carried by the synapses.
摘要翻译：提供神经等效电路，突触等效电路和电池体等效电路，从而再现根据神经细胞的生理功能和物理结构的电特性。模拟神经细胞电特性的神经等效电路，其中输入信号fin（t）和输出信号fout（t）满足由[数值式11]表示的关系，其中kP，kI和TI各自是确定的常数，N表示突触的总数，M表示由突触携带的第一发射机的种类的总数，L表示由突触携带的第二发射机的种类的总数。

75. 发明授权

US08078557B1 Use of neural networks for keyword generation 有权
标题翻译：使用神经网络进行关键字生成
公开(公告)号：US08078557B1
公开(公告)日：2011-12-13
申请号：US12472204
申请日：2009-05-26
申请人： Alexander V. Ershov
发明人： Alexander V. Ershov
IPC分类号： G06E1/00
CPC分类号： G06F17/30867 , Y10S707/99933 , Y10S707/99935 , Y10S707/99936
摘要： A system for identifying keywords in search results includes a plurality of neurons connected as a neural network, the neurons being associated with words and documents. An activity regulator regulates a minimum and/or maximum number of neurons of the neural network that are excited at any given time. Means for displaying the neurons to a user and identifying the neurons that correspond to keywords can be provided. Means for changing positions of the neurons relative to each other based on input from the user can be provided. The change in position of one neuron changes the keywords. The input from the user can be dragging a neuron on a display device, or changing a relevance of two neurons relative to each other. The neural network can be excited by a query that comprises words selected by a user. The neural network can be a bidirectional network. The user can inhibit neurons of the neural network by indicating irrelevance of a document. The neural network can be excited by a query that identifies a document considered relevant by a user. The neural network can also include neurons that represent groups of words. The neural network can be excited by a query that identifies a plurality of documents considered relevant by a user, and can output keywords associated with the plurality of documents.
摘要翻译：用于在搜索结果中识别关键词的系统包括连接为神经网络的多个神经元，神经元与单词和文档相关联。活动调节器调节在任何给定时间被激发的神经网络的最小和/或最大数量的神经元。可以提供用于向用户显示神经元并识别与关键字相对应的神经元的装置。可以提供用于基于来自用户的输入来改变神经元相对于彼此的位置的装置。一个神经元的位置变化改变了关键词。来自用户的输入可以拖动显示设备上的神经元，或者改变两个神经元相对于彼此的相关性。神经网络可以由包括用户选择的单词的查询激发。神经网络可以是双向网络。用户可以通过指示文档的不相关来抑制神经网络的神经元。可以通过识别用户认为相关的文档的查询激发神经网络。神经网络还可以包括表示单词组的神经元。神经网络可以通过识别由用户认为相关的多个文档的查询激发，并且可以输出与多个文档相关联的关键字。

76. 发明授权

US08065247B2 Systems and methods for multivariate influence analysis of heterogenous mixtures of categorical and continuous data 有权
标题翻译：用于分类和连续数据的异质混合物的多变量影响分析的系统和方法
公开(公告)号：US08065247B2
公开(公告)日：2011-11-22
申请号：US12115409
申请日：2008-05-05
申请人： Alan Schlottmann
发明人： Alan Schlottmann
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00
CPC分类号： G06N3/02
摘要： Systems, methods, and computer readable storage medium with executable instructions for detecting outliers and hidden relationships in heterogeneous data sets are provided. Features of the invention pertain to design and operation of various predictive models that identify multivariate outliers and influential observations by recognizing systematic local relationships within heterogeneous data sets or subpopulations of heterogeneous data sets. Multivariate outliers and influential observations are identified by utilizing general distance metrics which are specific to and defined for any number of individual observations within heterogeneous data sets. Aspects of the invention may be applied to sets of data that are large and complex (e.g. loan portfolios, health insurance company data, homeland security profiles, etc.) or sets of data having a more-limited scope (e.g. medical or drug research, etc.).
摘要翻译：提供了具有用于检测异构数据集中的异常值和隐藏关系的可执行指令的系统，方法和计算机可读存储介质。本发明的特征涉及各种预测模型的设计和操作，其通过识别异构数据集或异构数据集的子群体内的系统局部关系来识别多变量异常值和有影响的观察值。通过利用一般距离度量来识别多变量异常值和有影响力的观测值，这些距离指标是针对异构数据集中的任意数量的个体观测而定义的。本发明的方面可以应用于大量且复杂的数据集合（例如，贷款组合，健康保险公司数据，国土安全简档等）或具有更有限范围的数据集（例如医疗或药物研究，等等。）。

77. 发明授权

US08051020B2 Base oil properties expert system 有权
标题翻译：基础油属性专家系统
公开(公告)号：US08051020B2
公开(公告)日：2011-11-01
申请号：US12336636
申请日：2008-12-17
申请人： Ajit Ramchandra Pradhan , John M. Rosenbaum , Nancy J. Bertrand , David C. Kramer , Allan G. Hee , Max I. Chang
发明人： Ajit Ramchandra Pradhan , John M. Rosenbaum , Nancy J. Bertrand , David C. Kramer , Allan G. Hee , Max I. Chang
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00 , G01N11/00
CPC分类号： G01N24/08 , G01N33/2888 , G01R33/44 , G01R33/4808 , G06F19/704 , G06F19/707
摘要： A method for predicting properties of lubricant base oil blends, comprising the steps of generating an NMR spectrum, HPLC-UV spectrum, and FIMS spectrum of a sample of a blend of at least two lubricant base oils and determining at least one composite structural molecular parameter of the sample from said spectrums. SIMDIST and HPO analyses of the sample are then generated in order to determine a composite boiling point distribution and molecular weight of the sample from such analysis. A composite structural molecular parameter is applied, and the composite boiling point distribution and the composite molecular weight to a trained neural network is trained to correlate with the composite structural molecular parameter composite boiling point distribution and the composite molecular weight so as to predict composite properties of the sample. The properties comprise Kinematic Viscosity at 40 C, Kinematic Viscosity at 100 C, Viscosity Index, Cloud Point, and Oxidation Performance.
摘要翻译：一种用于预测润滑剂基础油共混物的性质的方法，包括以下步骤：产生至少两种润滑剂基础油的共混物的样品的NMR光谱，HPLC-UV光谱和FIMS光谱，并确定至少一个复合结构分子参数来自所述光谱的样品。然后生成样品的SIMDIST和HPO分析，以便从这种分析确定样品的复合沸点分布和分子量。应用复合结构分子参数，对训练有素的神经网络的复合沸点分布和复合分子量进行了训练，与复合结构分子参数复合沸点分布和复合分子量相关，以预测复合材料的复合特性例子。性能包括40℃的运动粘度，100℃的运动粘度，粘度指数，浊点和氧化性能。

78. 发明授权

US08050717B2 Signal processing system and method for calibrating channel signals supplied from an array of sensors having different operating characteristics 有权
标题翻译：用于校准从具有不同操作特性的传感器阵列提供的信道信号的信号处理系统和方法
公开(公告)号：US08050717B2
公开(公告)日：2011-11-01
申请号：US11514204
申请日：2006-09-01
申请人： Akihiko Sugiyama
发明人： Akihiko Sugiyama
IPC分类号： H04B1/38 , H04R3/00 , G01R1/02 , G06E1/00
CPC分类号： H04R1/406 , H04B17/21 , H04R3/005 , H04R2201/401 , H04R2201/403 , H04R2430/25
摘要： In a signal processing system, a set of channel signals from an array of sensors of different operating characteristics are processed in calibration circuitry that calculates individual average values of the channel signals and calculates an average of the individual average values of channel signals as a reference value. Reciprocal calculators calculate reciprocal values of the individual average values of the channel signals. Scaling circuitry scales the reciprocal values by the reference value to produce a set of amplitude calibration signals and scales the channel signals by the calibration signals respectively. As a result, the channel signals are normalized by their own average values and scaled by the reference value to produce a set of calibrated channel signals.
摘要翻译：在信号处理系统中，来自不同操作特性的传感器阵列的一组通道信号在校准电路中被处理，该校准电路计算通道信号的各个平均值，并且计算通道信号的各个平均值的平均值作为参考值。互惠计算器计算通道信号的各个平均值的互逆值。缩放电路将互逆值缩放参考值，以产生一组幅度校准信号，并分别用校准信号对信道信号进行缩放。结果，信道信号通过它们自己的平均值被归一化并且被参考值缩放以产生一组校准的信道信号。

79. 发明授权

US08041662B2 Domain name geometrical classification using character-based n-grams 有权
标题翻译：使用基于字符的n-gram的域名几何分类
公开(公告)号：US08041662B2
公开(公告)日：2011-10-18
申请号：US11837482
申请日：2007-08-10
申请人： Ilia Reznik , Roger N. Simonson
发明人： Ilia Reznik , Roger N. Simonson
IPC分类号： G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00
CPC分类号： G06F17/30707 , G06F17/30887
摘要： Character-based n-grams are derived from a domain name in order to classify such domain name in pre-established categories. Domain name character-based n-grams are mapped to vector points in a multidimensional space, where the number of dimensions is the number of different n-grams that can exist for an n-character combination. The relationship between the domain name vector point and the vector points of the various other domain names is used to classify the domain name vector point. The classification system can use statistical methods using relative frequencies of character-based n-grams in various classifications as indicators. A dictionary set of character-based n-grams can be derived from one or more domain names and associated with probability indicating the likelihood that the character-based n-gram is found in a domain name of a given classification. Such probability can be an estimator of a classification of a new domain name having such character-based n-gram.
摘要翻译：基于字符的n-gram来自域名，以便将这样的域名分类到预先建立的类别中。基于域名的基于字符的n-gram被映射到多维空间中的向量点，其中维数是n个字符组合可以存在的不同n-gram的数量。域名向量点和各种其他域名的向量点之间的关系用于对域名向量点进行分类。分类系统可以使用在各种分类中使用基于字符的n-gram的相对频率的统计方法作为指标。基于字符的n-gram的字典集可以从一个或多个域名导出，并与指示在给定分类的域名中找到基于字符的n-gram的可能性相关联。这种概率可以是具有这种基于字符的n-gram的新域名的分类的估计。

80. 发明授权

US08032483B1 Using game responses to gather data 有权
标题翻译：使用游戏响应来收集数据
公开(公告)号：US08032483B1
公开(公告)日：2011-10-04
申请号：US11169279
申请日：2005-06-29
申请人： Taher Haveliwala , Benedict Gomes , Amitabh K. Singhal
发明人： Taher Haveliwala , Benedict Gomes , Amitabh K. Singhal
IPC分类号： G06F7/00 , G06F17/00 , G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00 , G06N3/08
CPC分类号： G06Q30/02
摘要： A system provides images or questions to multiple game participants and receives labels or answers in response thereto. The system uses the labels or answers for various data gathering purposes.
摘要翻译：系统向多个游戏参与者提供图像或问题，并响应于此接收标签或答案。系统使用标签或答案进行各种数据收集。

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