专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明申请

US20070198507A1 System and Method For Modeling Multilabel Classification and Ranking 有权
标题翻译：用于建模多标签分类和排名的系统和方法
公开(公告)号：US20070198507A1
公开(公告)日：2007-08-23
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： G06F17/30
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。

2. 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。

3. 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。

4. 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。

5. 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）。

6. 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。

7. 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。

8. 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。

9. 发明授权

US07797265B2 Document clustering that applies a locality sensitive hashing function to a feature vector to obtain a limited set of candidate clusters 失效
标题翻译：文档聚类，其将特征向量应用局部敏感散列函数以获得有限的候选聚类集
公开(公告)号：US07797265B2
公开(公告)日：2010-09-14
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： 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 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。

10. 发明授权

US08005771B2 Segment-based change detection method in multivariate data stream 有权
标题翻译：多变量数据流中基于段的变化检测方法
公开(公告)号：US08005771B2
公开(公告)日：2011-08-23
申请号：US12236587
申请日：2008-09-24
申请人： Terrence Chen , Chao Yuan , Abdul Saboor Sheikh , Claus Neubauer
发明人： Terrence Chen , Chao Yuan , Abdul Saboor Sheikh , Claus Neubauer
IPC分类号： G06F15/18
CPC分类号： G06K9/00536 , G06K9/6284
摘要： A method and framework are described for detecting changes in a multivariate data stream. A training set is formed by sampling time windows in a data stream containing data reflecting normal conditions. A histogram is created to summarize each window of data, and data within the histograms are clustered to form test distribution representatives to minimize the bulk of training data. Test data is then summarized using histograms representing time windows of data and data within the test histograms are clustered. The test histograms are compared to the training histograms using nearest neighbor techniques on the clustered data. Distances from the test histograms to the test distribution representatives are compared to a threshold to identify anomalies.
摘要翻译：描述了用于检测多变量数据流中的变化的方法和框架。通过在包含反映正常条件的数据的数据流中采样时间窗口来形成训练集。创建直方图以总结每个数据窗口，并且将直方图中的数据进行聚类以形成测试分发代表以最小化训练数据的大部分。然后使用表示数据的时间窗口的直方图来汇总测试数据，并且将测试直方图中的数据聚类。将测试直方图与使用最近邻技术的聚类数据的训练直方图进行比较。将测试直方图与测试分布代表的距离与阈值进行比较以识别异常。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式