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公开(公告)号：US07200267B1
公开(公告)日：2007-04-03
申请号：US11324444
申请日：2005-12-30
CPC分类号： G06K9/00422 , G06K9/6296
摘要： The invention performs handwriting recognition using mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. Each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of its states. The MBNs encode the probabilities of observing the sets of visual observations corresponding to a handwritten character. Each of the HSBNs encodes the probabilities of observing the sets of visual observations corresponding to a handwritten character and given a hidden common variable being in a particular state.
摘要翻译： 本发明使用贝叶斯网络的混合来执行手写识别。 贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。 常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 每个HSBN在假设下共同的外部隐藏变量处于相应的一个状态的模型中模拟世界。 MBN编码观察对应于手写字符的视觉观察组的概率。 每个HSBN编码观察对应于手写字符的视觉观察组的概率，并给出处于特定状态的隐藏的公共变量。
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公开(公告)号：US07162489B2
公开(公告)日：2007-01-09
申请号：US11299539
申请日：2005-12-12
IPC分类号： G06F7/00
CPC分类号： G06F17/30592 , G06N7/00 , Y10S707/957 , Y10S707/958 , Y10S707/99943
摘要： The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a “data tube” from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot tables and/or OLAP cubes. It determines if data substantially deviates from a predicted value established by a curve fitting process such as, for example, a piece-wise linear function applied to the data tube. A threshold value can also be employed by the present invention to facilitate in determining a degree of deviation necessary before a data value is considered anomalous. The threshold value can be supplied dynamically and/or statically by a system and/or a user via a user interface. Additionally, the present invention provides an indication to a user of the type and location of a detected anomaly from a top level data perspective.
摘要翻译： 本发明利用曲线拟合数据技术从数据角度提供“数据管”中的数据异常的自动检测，从而允许例如检测诸如屏幕上的数据异常，向下钻取和钻取数据异常的数据异常 例如，枢轴表和/或OLAP多维数据集。 它确定数据是否基本上偏离由曲线拟合处理（例如应用于数据管的分段线性函数）所建立的预测值。 本发明也可以采用阈值，以便在确定数据值被认为是异常之前确定所需的偏差程度。 阈值可以由系统和/或用户经由用户界面动态地和/或静态地提供。 另外，本发明从顶级数据的角度向用户提供了检测到的异常的类型和位置的指示。
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公开(公告)号：US06405200B1
公开(公告)日：2002-06-11
申请号：US09298584
申请日：1999-04-23
申请人： David E. Heckerman
发明人： David E. Heckerman
IPC分类号： G06F1730
CPC分类号： G06F17/3089 , Y10S707/99936 , Y10S707/99944
摘要： Generation of a model for raw variables from a model for cooked variables. In one embodiment, a first data model for a plurality of cooked transactional variables is input. The cooked transactional variables have been abstracted from raw transactional variables, where the latter variables are based on a data set comprising a plurality of records, each record having a value for each raw transactional variables. A type of the first model is determined, and a second data model, for the plurality of raw transactional variables, is generated based on the first data model and the type of the first data model. The second data model is then output.
摘要翻译： 从熟化变量的模型生成原始变量的模型。 在一个实施例中，输入用于多个烹饪事务变量的第一数据模型。 熟习的事务变量已经从原始事务变量中抽象出来，后者变量基于包含多个记录的数据集，每个记录具有每个原始事务变量的值。 确定第一模型的类型，并且基于第一数据模型和第一数据模型的类型来生成用于多个原始事务变量的第二数据模型。 然后输出第二个数据模型。
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74.发明授权公开(公告)号：US06263308B1
公开(公告)日：2001-07-17
申请号：US09531055
申请日：2000-03-20
申请人： David E. Heckerman , Fileno A. Alleva , Robert L. Rounthwaite , Daniel Rosen , Mei-Yuh Hwang , Yoram Yaacovi , John L. Manferdelli
发明人： David E. Heckerman , Fileno A. Alleva , Robert L. Rounthwaite , Daniel Rosen , Mei-Yuh Hwang , Yoram Yaacovi , John L. Manferdelli
IPC分类号： G10L1502
CPC分类号： G10L15/063
摘要： Automated methods and apparatus for synchronizing audio and text data, e.g., in the form of electronic files, representing audio and text expressions of the same work or information are described. Also described are automated methods of detecting errors and other discrepancies between the audio and text versions of the same work. A speech recognition operation is performed on the audio data initially using a speaker independent acoustic model. The recognized text in addition to audio time stamps are produced by the speech recognition operation. The recognized text is compared to the text in text data to identify correctly recognized words. The acoustic model is then retrained using the correctly recognized text and corresponding audio segments from the audio data transforming the initial acoustic model into a speaker trained acoustic model. The retrained acoustic model is then used to perform an additional speech recognition operation on the audio data. The audio and text data are synchronized using the results of the updated acoustic model. In addition, one or more error reports based on the final recognition results are generated showing discrepancies between the recognized words and the words included in the text. By retraining the acoustic model in the above described manner, improved accuracy is achieved.
摘要翻译： 描述用于同步音频和文本数据的自动方法和装置，例如以电子文件的形式，表示相同作品或信息的音频和文本表达。 还描述了检测相同作品的音频和文本版本之间的错误和其他差异的自动化方法。 首先使用与扬声器无关的声学模型对音频数据执行语音识别操作。 通过语音识别操作产生除音频时间戳之外的识别文本。 将识别的文本与文本数据中的文本进行比较，以识别正确识别的字词。 然后使用来自音频数据的正确识别的文本和对应的音频段将声学模型再训练，将初始声学模型变换成扬声器训练的声学模型。 然后再训练的声学模型用于对音频数据执行附加的语音识别操作。 使用更新的声学模型的结果来同步音频和文本数据。 此外，生成基于最终识别结果的一个或多个错误报告，显示识别的单词与文本中包含的单词之间的差异。 通过以上述方式重新训练声学模型，实现了提高的精度。
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公开(公告)号：US06260035B1
公开(公告)日：2001-07-10
申请号：US09197159
申请日：1998-11-20
申请人： Eric Horvitz , John S. Breese , David E. Heckerman , Samuel D. Hobson , David O. Hovel , Adrian C. Klein , Jacobus A. Rommelse , Gregory L. Shaw
发明人： Eric Horvitz , John S. Breese , David E. Heckerman , Samuel D. Hobson , David O. Hovel , Adrian C. Klein , Jacobus A. Rommelse , Gregory L. Shaw
IPC分类号： G06F1700
CPC分类号： G06N5/00 , G06F9/453 , Y10S707/99943
摘要： A general event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool allows for rapid development of a general event processor that creates high-level events from combinations of user actions. The event system, in combination with a reasoning system, is able to monitor and perform inference about several classes of events for a variety of purposes. The various classes of events include the current context, the state of key data structures in a program, general sequences of user inputs, including actions with a mouse-controlled cursor while interacting with a graphical user interface, words typed in free-text queries for assistance, visual information about users, such as gaze and gesture information, and speech information. Additionally, a method is provided for building an intelligent user interface system by constructing a reasoning model to compute the probability of alternative user's intentions, goals, or informational needs through analysis of information about a user's actions, program state, and words. The intelligent user interface system monitors user interaction with a software application and applies probabilistic reasoning to sense that the user may need assistance in using a particular feature or to accomplish a specific task. The intelligent user interface also accepts a free-text query from the user asking for help and combines the inference analysis of user actions and program state with an inference analysis of the free-text query. The inference system accesses a rich, updatable user profile system to continually check for competencies and changes assistance that is given based on user competence.
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公开(公告)号：US6021403A
公开(公告)日：2000-02-01
申请号：US684003
申请日：1996-07-19
申请人： Eric Horvitz , John S. Breese , David E. Heckerman , Samuel D. Hobson , David O. Hovel , Adrian C. Klein , Jacobus A. Rommelse , Gregory L. Shaw
发明人： Eric Horvitz , John S. Breese , David E. Heckerman , Samuel D. Hobson , David O. Hovel , Adrian C. Klein , Jacobus A. Rommelse , Gregory L. Shaw
CPC分类号： G06N5/00 , G06F9/4446 , Y10S707/99943
摘要： An event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool, contained in the system, allows for rapidly developing a general event processor that creates high-level events from combinations of user actions. An event system, in combination with an inference system, monitors and infers, for various purposes, about several classes of events including: current program context; state of key data structures; user input sequences, including actions with a mouse-controlled cursor while interacting with a graphical user interface; words typed in free-text help queries; visual user information, such as gaze and gesture information; and user speech information. Additionally, an intelligent user interface is provided by constructing a reasoning model that computes probability of alternative user intentions, goals or information needs through analyzing information regarding program state, and that user's actions and free-text query words. Specifically, the interface monitors user interaction with a program and probabilistically reasons to sense that a user may need assistance in using a particular feature or to accomplish a specific task. This interface accepts a free-text help query from the user and combines the inference analysis of user actions and the program state with an inference analysis of the query. The inference system, using an updateable user profile, continually checks for user competencies and, based on such competencies, changes assistance that is offered.
摘要翻译： 一个事件组合和监控系统，允许从低级别事件的组合创建高级别事件。 包含在系统中的事件规范工具允许快速开发通用事件处理器，它通过用户操作的组合创建高级事件。 事件系统与推理系统相结合，针对各种目的监视和推测几类事件，包括：当前程序环境; 关键数据结构状态; 用户输入序列，包括与图形用户界面交互时具有鼠标控制的光标的动作; 输入自由文本帮助查询的单词; 视觉用户信息，如凝视和姿态信息; 和用户语音信息。 另外，通过构建推理模型来提供智能用户界面，该推理模型通过分析关于程序状态的信息以及该用户的动作和自由文本查询词来计算替代用户意图，目标或信息需求的概率。 具体来说，接口监视用户与程序的交互，并且概率地认为用户可能需要协助使用特定特征或完成特定任务。 该接口接受来自用户的自由文本帮助查询，并将用户操作的推理分析和程序状态与查询的推断分析相结合。 推理系统使用可更新的用户配置文件，不断检查用户能力，并根据这些能力来更改提供的帮助。
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公开(公告)号：US5715374A
公开(公告)日：1998-02-03
申请号：US267798
申请日：1994-06-29
CPC分类号： G06N5/025
摘要： An improved method and system for performing case-based reasoning is provided. A belief network is utilized by the preferred case-based reasoning system for assisting a user in problem resolution. After resolving a problem of a user, the preferred embodiment of the present invention updates the probabilities in the belief network so as to provide for a more accurate problem resolution upon the next invocation of the preferred embodiment. The belief network of the preferred embodiment contains six data types relating to a problem resolution scenario. The data types utilized by the belief network of the preferred embodiment include: issues, causes, resolutions, symptoms, terms, and alternates.
摘要翻译： 提供了一种用于执行基于案例推理的改进方法和系统。 信仰网络被优选的基于情况的推理系统用于帮助用户解决问题。 在解决用户的问题之后，本发明的优选实施例更新信念网络中的概率，以便在下一次优选实施例的调用时提供更准确的问题解决。 优选实施例的信念网络包含与问题解决方案相关的六种数据类型。 由优选实施例的信念网络使用的数据类型包括：问题，原因，解决方案，症状，术语和替代。
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公开(公告)号：US5704017A
公开(公告)日：1997-12-30
申请号：US602238
申请日：1996-02-16
CPC分类号： H04N21/252 , G06Q30/02
摘要： The disclosed system provides an improved collaborative filtering system by utilizing a belief network, which is sometimes known as a Bayesian network. The disclosed system learns a belief network using both prior knowledge obtained from an expert in a given field of decision making and a database containing empirical data obtained from many people. The empirical data contains attributes of users as well as their preferences in the field of decision making. After initially learning the belief network, the belief network is relearned at various intervals when additional attributes are identified as having a causal effect on the preferences and data for these additional attributes can be gathered. This relearning allows the belief network to improve its accuracy at predicting preferences of a user. Upon each iteration of relearning, a cluster model is automatically generated that best predicts the data in the database. After relearning the belief network a number of times, the belief network is used to predict the preferences of a user using probabilistic inference. In performing probabilistic inference, the known attributes of a user are received and the belief network is accessed to determine the probability of the unknown preferences of the user given the known attributes. Based on these probabilities, the preference most likely to be desired by the user can be predicted.
摘要翻译： 所公开的系统通过利用有时被称为贝叶斯网络的置信网络来提供改进的协同过滤系统。 所公开的系统使用从给定的决策领域的专家获得的现有知识和包含从许多人获得的经验数据的数据库来学习信念网络。 实证数据包含用户的属性以及决策领域的偏好。 在最初学习信念网络之后，当附加属性被识别为对偏好具有因果影响并且可以收集这些附加属性的数据时，信念网络以不同的间隔被重新学习。 这种再学习允许信念网络在预测用户的偏好时提高其准确性。 在重新学习的每次迭代之后，自动生成最能预测数据库中的数据的集群模型。 在重新学习信念网络多次之后，信念网络用于使用概率推理来预测用户的偏好。 在执行概率推理时，接收用户的已知属性，并且访问置信网络以确定给定已知属性的用户的未知偏好的概率。 基于这些概率，可以预测用户最可能希望的偏好。
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公开(公告)号：US5694559A
公开(公告)日：1997-12-02
申请号：US400797
申请日：1995-03-07
申请人： Samuel D. Hobson , Eric Horvitz , David E. Heckerman , John S. Breese , Erich-S.o slashed.ren Finkelstein , Gregory L. Shaw , James R. Flynn , Karen Jensen
发明人： Samuel D. Hobson , Eric Horvitz , David E. Heckerman , John S. Breese , Erich-S.o slashed.ren Finkelstein , Gregory L. Shaw , James R. Flynn , Karen Jensen
CPC分类号： G06F17/30672 , G06F17/30687 , G06F9/4446 , G06F9/4448 , Y10S707/99933
摘要： An improved free text query method and system is provided as part of an improved on-line help system. In a preferred embodiment of the present invention, the on-line help system provides a free text query system that performs partial analysis. The partial analysis performed by the preferred embodiment includes identifying keywords within input provided by the user, performing disambiguation analysis, performing definiteness analysis, performing capitalization analysis, and generating a ranked list of candidates according to a probability associated with each candidate. In addition, the preferred embodiment of the present invention is internationalizable. That is, the present invention is easily ported between different languages.
摘要翻译： 提供了一种改进的自由文本查询方法和系统，作为改进的在线帮助系统的一部分。 在本发明的优选实施例中，在线帮助系统提供执行部分分析的自由文本查询系统。 由优选实施例执行的部分分析包括识别由用户提供的输入内的关键字，执行消歧分析，执行确定性分析，执行大小写分析，以及根据与每个候选相关联的概率生成候选排序列表。 此外，本发明的优选实施例是可国际化的。 也就是说，本发明容易地在不同语言之间移植。
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公开(公告)号：US08706421B2
公开(公告)日：2014-04-22
申请号：US11738411
申请日：2007-04-20
摘要： Shift invariant predictors are described herein. By way of example, a system for predicting binding information relating to a binding of a protein and a ligand can include a trained binding model and a prediction component. The trained binding model can include a hidden variable representing an unknown alignment of the ligand at a binding site of the protein. The prediction component can be configured to predict the binding information by employing information about the protein's sequence, the ligand's sequence and the trained binding model.
摘要翻译： 这里描述了移位不变量预测器。 作为示例，用于预测与蛋白质和配体的结合相关的结合信息的系统可以包括训练的结合模型和预测组分。 经训练的结合模型可以包括表示蛋白质结合位点处配体的未知比对的隐藏变量。 预测组件可以被配置为通过使用关于蛋白质序列，配体序列和训练的结合模型的信息来预测结合信息。
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