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51. 发明申请

US20080205775A1 Online document clustering 失效
标题翻译：在线文档聚类
公开(公告)号：US20080205775A1
公开(公告)日：2008-08-28
申请号：US12072254
申请日：2008-02-25
申请人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
发明人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
IPC分类号： G06K9/62
CPC分类号： G06F17/30707
摘要： Documents from a data stream are clustered by first generating a feature vector for each document. A set of cluster centroids (e.g., feature vectors of their corresponding clusters) are retrieved from a memory based on the feature vector of the document and a relative age of each of the cluster centroids. The centroids may be retrieved by retrieving a set of cluster identifiers from a cluster table, the cluster identifiers each indicative of a respective cluster centroid, and retrieving the cluster centroids corresponding to the retrieved cluster identifiers from a memory. A list of cluster identifiers in the cluster table may be maintained based on the relative age of cluster centroids corresponding to the cluster identifiers. Cluster identifiers that correspond to cluster centroids with a relative age exceeding a predetermined threshold are periodically removed from the list of cluster identifiers.
摘要翻译：通过首先为每个文档生成特征向量来聚集来自数据流的文档。基于文档的特征向量和每个聚类中心的相对年龄，从存储器中检索一组聚类中心（例如，其对应的聚类的特征向量）。可以通过从集群表中检索一组集群标识符来检索质心，每个集群标识符指示相应的集群质心，并且从存储器中检索与所检索的集群标识符相对应的集群质心。可以基于与集群标识符对应的集群质心的相对年龄来维护集群表中的集群标识符的列表。对应于具有相对年龄超过预定阈值的聚类中心的群集标识符周期性地从群集标识符列表中移除。

52. 发明申请

US20070005257A1 Bayesian network frameworks for biomedical data mining 审中-公开
标题翻译：用于生物医学数据挖掘的贝叶斯网络框架
公开(公告)号：US20070005257A1
公开(公告)日：2007-01-04
申请号：US11110496
申请日：2005-07-25
申请人： Jie Cheng , Claus Neubauer
发明人： Jie Cheng , Claus Neubauer
IPC分类号： G06F19/00
CPC分类号： G06K9/6296
摘要： A system and method for data classification are provided, the system including a processor, an adapter in signal communication with the processor for receiving data, a filtering unit in signal communication with the processor for pre-processing the data and filtering features of the data, a selection unit in signal communication with the processor for learning a Bayesian network (BN) classifier and selecting features responsive to the BN classifier, and an evaluation unit in signal communication with the processor for evaluating a model responsive to the BN classifier; and the method including receiving data, pre-processing the data, filtering features of the data, learning a BN classifier, selecting features responsive to the BN classifier, and evaluating a model responsive to the BN classifier.
摘要翻译：提供了一种用于数据分类的系统和方法，该系统包括处理器，与处理器进行信号通信的适配器，用于接收数据;滤波单元，与处理器进行信号通信，用于预处理数据和滤波数据的特征; 与所述处理器进行信号通信的选择单元，用于学习贝叶斯网络（BN）分类器并响应于所述BN分类器选择特征;以及评估单元，用于与所述处理器进行信号通信以评估响应于所述BN分类器的模型; 并且该方法包括接收数据，预处理数据，过滤数据的特征，学习BN分类器，响应于BN分类器选择特征，以及响应于BN分类器来评估模型。

53. 发明授权

US07860818B2 System and method for case-based multilabel classification and ranking 有权
标题翻译：基于案例的多标签分类和排序的系统和方法
公开(公告)号：US07860818B2
公开(公告)日：2010-12-28
申请号：US11764824
申请日：2007-06-19
申请人： Klaus Brinker , Claus Neubauer
发明人： Klaus Brinker , Claus Neubauer
IPC分类号： G06N5/00
CPC分类号： G05B23/0229 , G06K9/6284 , G06N99/005
摘要： The present invention provides methods and apparatus for determining and utilizing case-based ranking methods, such as methods for machine condition monitoring. Specifically, the present invention provides a method for identifying and prioritizing labeled data. The method allows a monitored system to be associated with a calibrated and ordered set of states. Further, in machine condition monitoring, the machine condition is associated with the entire set of states in a particular order with one or more relevance zero-points. That is, a ranked set of calibrated data describing machine conditions is augmented with an annotation indicating a cut-off between relevant and non-relevant data.
摘要翻译：本发明提供了用于确定和利用基于案例的排序方法的方法和装置，例如机器状态监视的方法。具体地，本发明提供了一种用于识别和标记数据的优先级的方法。该方法允许被监视系统与校准的和有序的状态集相关联。此外，在机器状态监视中，机器状态与具有一个或多个相关性零点的特定顺序的整个状态集相关联。也就是说，描述机器状况的一系列校准数据被增加，其中注释指示相关数据和非相关数据之间的截止。

54. 发明授权

US07711668B2 Online document clustering using TFIDF and predefined time windows 失效
标题翻译：使用TFIDF和预定义时间窗口的在线文档集群
公开(公告)号：US07711668B2
公开(公告)日：2010-05-04
申请号：US12072254
申请日：2008-02-25
申请人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
发明人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
IPC分类号： G06N5/00
CPC分类号： G06F17/30707
摘要： Documents from a data stream are clustered by first generating a feature vector for each document. A set of cluster centroids (e.g., feature vectors of their corresponding clusters) are retrieved from a memory based on the feature vector of the document and a relative age of each of the cluster centroids. The centroids may be retrieved by retrieving a set of cluster identifiers from a cluster table, the cluster identifiers each indicative of a respective cluster centroid, and retrieving the cluster centroids corresponding to the retrieved cluster identifiers from a memory. A list of cluster identifiers in the cluster table may be maintained based on the relative age of cluster centroids corresponding to the cluster identifiers. Cluster identifiers that correspond to cluster centroids with a relative age exceeding a predetermined threshold are periodically removed from the list of cluster identifiers.
摘要翻译：通过首先为每个文档生成特征向量来聚集来自数据流的文档。基于文档的特征向量和每个聚类中心的相对年龄，从存储器中检索一组聚类中心（例如，其对应的聚类的特征向量）。可以通过从集群表中检索一组集群标识符来检索质心，每个集群标识符指示相应的集群质心，并且从存储器中检索与所检索的集群标识符相对应的集群质心。可以基于与集群标识符对应的集群质心的相对年龄来维护集群表中的集群标识符的列表。对应于具有相对年龄超过预定阈值的聚类中心的群集标识符周期性地从群集标识符列表中移除。

55. 发明申请

US20080208847A1 Relevance ranking for document retrieval 审中-公开
标题翻译：文件检索的相关性排名
公开(公告)号：US20080208847A1
公开(公告)日：2008-08-28
申请号：US12072222
申请日：2008-02-25
申请人： Fabian Moerchen , Klaus Brinker , Claus Neubauer
发明人： Fabian Moerchen , Klaus Brinker , Claus Neubauer
IPC分类号： G06F17/30
CPC分类号： G06F16/338 , G06F16/313
摘要： Documents and/or document clusters are ranked with respect to their geographical locations and/or user specific (e.g., user input) relevance. Highly relevant documents and/or document clusters are assigned higher ranks than less relevant documents and/or clusters. In this way, ranked lists of documents and/or clusters, top clusters (e.g., top stories), top documents (e.g., most important articles), etc. may be served (e.g., presented, delivered, etc.) to users.
摘要翻译：文档和/或文档集合相对于其地理位置和/或用户特定（例如，用户输入）相关性进行排名。高度相关的文档和/或文档集群被分配比较少的相关文档和/或集群更高的级别。以这种方式，可以向用户提供文档和/或群集的排名列表，顶级群组（例如，顶级故事），顶级文档（例如，最重要的文章）等（例如呈现，传递等）。

56. 发明申请

US20080205774A1 Document clustering using a locality sensitive hashing function 失效
标题翻译：使用局部敏感散列函数进行文档聚类
公开(公告)号：US20080205774A1
公开(公告)日：2008-08-28
申请号：US12072179
申请日：2008-02-25
申请人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
发明人： Klaus Brinker , Fabian Moerchen , Bernhard Glomann , Claus Neubauer
IPC分类号： G06K9/62
CPC分类号： G06F17/30707
摘要： Documents from a data stream are clustered by first generating a feature vector for each document. A set of cluster centroids (e.g., feature vectors of their corresponding clusters) are retrieved from a memory based on the feature vector of the document using a locality sensitive hashing function. The centroids may be retrieved by retrieving a set of cluster identifiers from a cluster table, the cluster identifiers each indicative of a respective cluster centroid, and retrieving the cluster centroids corresponding to the retrieved cluster identifiers from a memory. Documents may then be clustered into one or more of the candidate clusters using distance measures from the feature vector of the document to the cluster centroids.
摘要翻译：通过首先为每个文档生成特征向量来聚集来自数据流的文档。基于使用位置敏感散列函数的文档的特征向量，从存储器检索集合中心集合（例如，其对应的集群的特征向量）。可以通过从集群表中检索一组集群标识符来检索质心，每个集群标识符指示相应的集群质心，并且从存储器中检索与所检索的集群标识符相对应的集群质心。然后可以使用从文档的特征向量到聚类中心的距离度量将文档聚类成一个或多个候选聚类。

57. 发明申请

US20080010226A1 System and Method for Case-Based Multilabel Classification and Ranking 有权
标题翻译：基于案例的多标签分类和排名的系统与方法
公开(公告)号：US20080010226A1
公开(公告)日：2008-01-10
申请号：US11764824
申请日：2007-06-19
申请人： Klaus Brinker , Claus Neubauer
发明人： Klaus Brinker , Claus Neubauer
IPC分类号： G06F15/18
CPC分类号： G05B23/0229 , G06K9/6284 , G06N99/005
摘要： The present invention provides methods and apparatus for determining and utilizing case-based ranking methods, such as methods for machine condition monitoring. Specifically, the present invention provides a method for identifying and prioritizing labeled data. The method allows a monitored system to be associated with a calibrated and ordered set of states. Further, in machine condition monitoring, the machine condition is associated with the entire set of states in a particular order with one or more relevance zero-points That is, a ranked set of calibrated data describing machine conditions is augmented with an annotation indicating a cut-off between relevant and non-relevant data.
摘要翻译：本发明提供了用于确定和利用基于案例的排序方法的方法和装置，例如机器状态监视的方法。具体地，本发明提供了一种用于识别和标记数据的优先级的方法。该方法允许被监视系统与校准的和有序的状态集相关联。此外，在机器状态监视中，机器状态与具有一个或多个相关性零点的特定顺序的整个状态集合相关联，即，描述机器状态的一组排列的校准数据用指示切割的注释来增加在相关和非相关数据之间。

58. 发明申请

US20060045207A1 Peak detection in mass spectroscopy data analysis 审中-公开
标题翻译：质谱数据分析中的峰值检测
公开(公告)号：US20060045207A1
公开(公告)日：2006-03-02
申请号：US11180342
申请日：2005-07-13
申请人： Jie Cheng , Claus Neubauer
发明人： Jie Cheng , Claus Neubauer
IPC分类号： H04L25/06
CPC分类号： H01J49/0036
摘要： A computer-implemented method for extracting peak information including providing a data spectrum, normalizing the data spectrum, binning features for reducing the resolution of the data spectrum and filtering noise from a normalized data spectrum, identifying at least one peak in the normalized data spectrum, performing a baseline correction of the at least one peak, and performing data mining on the at least one peak to determine a pathology.
摘要翻译：一种计算机实现的方法，用于提取峰值信息，包括提供数据频谱，归一化数据频谱，合并特征，用于降低数据频谱的分辨率，并从标准化数据频谱滤除噪声，识别归一化数据频谱中的至少一个峰值，执行所述至少一个峰值的基线校正，以及对所述至少一个峰值执行数据挖掘以确定病理学。

59. 发明授权

US08744807B2 Scalable and extensible framework for storing and analyzing sensor data 失效
标题翻译：可扩展和可扩展的框架，用于存储和分析传感器数据
公开(公告)号：US08744807B2
公开(公告)日：2014-06-03
申请号：US12781890
申请日：2010-05-18
申请人： Mathaeus Dejori , Ciprian Raileanu , Nazif Cihan Tas , Claus Neubauer
发明人： Mathaeus Dejori , Ciprian Raileanu , Nazif Cihan Tas , Claus Neubauer
IPC分类号： G06F17/40 , G06F11/34 , G06F9/445 , G01D9/00
CPC分类号： G06F11/3476 , G01D9/005 , G06F9/44526
摘要： In a framework for acquiring and analyzing data from a network of sensors, plug-in software interfaces are used to provide scalability and flexibility. Data collection set-up data is exchanged through one or more first plug-in software interfaces with data collection devices, to configure the processor to collect measurement data from the data collection devices. Analysis set-up data is exchanged through one or more second plug-in software interfaces with one or more data analysis software packages, to configure the processor to provide a predefined subset of the measurement data to the data analysis software packages and to accept analysis results from the data analysis software packages. Measurement data and analysis results are subsequently exchanged through the plug-in interfaces.
摘要翻译：在用于从传感器网络获取和分析数据的框架中，使用插件软件接口来提供可扩展性和灵活性。数据收集设置数据通过与数据采集设备的一个或多个第一插件软件接口进行交换，以配置处理器从数据采集设备收集测量数据。分析设置数据通过一个或多个第二插件软件接口与一个或多个数据分析软件包交换，以配置处理器向数据分析软件包提供测量数据的预定义子集并接受分析结果从数据分析软件包中。随后通过插件接口交换测量数据和分析结果。

60. 发明授权

US08200592B2 System and method for modeling multilabel classification and ranking 有权
标题翻译：多层分类和排序建模的系统和方法
公开(公告)号：US08200592B2
公开(公告)日：2012-06-12
申请号：US11668676
申请日：2007-01-30
申请人： Klaus Brinker , Claus Neubauer
发明人： Klaus Brinker , Claus Neubauer
IPC分类号： G06N5/00
CPC分类号： G05B13/048 , G05B23/0245
摘要： The present invention provides methods and apparatus for determining and utilizing detection models, such as models for machine condition monitoring. Specifically, the present invention provides a method for identifying and prioritizing labeled data. The model allows a monitored system to be associated with a calibrated and ordered set of states. Further, in machine condition monitoring, the machine condition is associated with the entire set of states in a particular order with a relevance zero-point. That is, a ranked set of calibrated data describing machine conditions is augmented with an annotation indicating a cut-off between relevant and non-relevant data.
摘要翻译：本发明提供了用于确定和利用检测模型的方法和装置，例如用于机器状态监测的模型。具体地，本发明提供了一种用于识别和标记数据的优先级的方法。该模型允许被监视的系统与校准的和有序的状态集相关联。此外，在机器状态监视中，机器状态与具有相关性零点的特定顺序的整个状态集相关联。也就是说，描述机器状况的一系列校准数据被增加，其中注释指示相关数据和非相关数据之间的截止。

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