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. 发明授权

US11372869B2 Frequent pattern mining 有权
公开(公告)号：US11372869B2
公开(公告)日：2022-06-28
申请号：US15995864
申请日：2018-06-01
申请人： Microsoft Technology Licensing, LLC
发明人： Shi Han , Yingnong Dang , Dongmei Zhang , Song Ge
IPC分类号： G06F17/30 , G06F16/2458 , G06F16/21 , H04L67/10
摘要： A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

2. 发明授权

US10747950B2 Automatic insights for spreadsheets 有权
公开(公告)号：US10747950B2
公开(公告)日：2020-08-18
申请号：US15115439
申请日：2014-01-30
申请人： Microsoft Technology Licensing, LLC.
发明人： Yingnong Dang , Shusen Liu , Xiao Liang , Haidong Zhang , Jim Sun , Dongmei Zhang , Scott Ruble
IPC分类号： G06F40/18 , G06F40/40 , G06Q10/06 , G06Q30/02
摘要： Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights from the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance in automatically generate charts that visually describe each insight and in natural language text that describes each insight in such a way that it may be understandable to a general audience who may not have a familiarity with statistics.

3. 发明授权

US10176246B2 Fast grouping of time series 有权
公开(公告)号：US10176246B2
公开(公告)日：2019-01-08
申请号：US14898216
申请日：2013-06-14
申请人： Microsoft Technology Licensing, LLC
发明人： Yingnong Dang , Qiang Wang , Qianchuan Zhao , Shulei Wang , Rui Ding , Qiang Fu , Dongmei Zhang
IPC分类号： G06F17/00 , G06F17/30 , G06F17/18 , G06K9/00 , G06K9/62
摘要： In some examples, a time-series data set can be analyzed and grouped in a fast and efficient manner. For instance, fast grouping of multiple time-series into clusters can be implemented through data reduction, determining cluster population, and fast matching by locality sensitive hashing. In some situations, a user can select a level of granularity for grouping time-series into clusters, which can involve trade-offs between the number of clusters and the maximum distance between two time-series in a cluster.

4. 发明申请

US20170177559A1 AUTOMATIC INSIGHTS FOR SPREADSHEETS 审中-公开
公开(公告)号：US20170177559A1
公开(公告)日：2017-06-22
申请号：US15115439
申请日：2014-01-30
申请人： Microsoft Technology Licensing, LLC.
发明人： Yingnong Dang , Shusen Liu , Xiao Liang , Haidong Zhang , Jim Sun , Dongmei Zhang , Scott Ruble
IPC分类号： G06F17/24 , G06F17/28
摘要： Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights from the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance in automatically generate charts that visually describe each insight and in natural language text that describes each insight in such a way that it may be understandable to a general audience who may not have a familiarity with statistics.

5. 发明授权

US09459947B2 Error report processing using call stack similarity 有权
公开(公告)号：US09459947B2
公开(公告)日：2016-10-04
申请号：US14594267
申请日：2015-01-12
申请人： Microsoft Technology Licensing, LLC.
发明人： Dongmei Zhang , Yingnong Dang , Song Ge
IPC分类号： G06F11/00 , G06F11/07
CPC分类号： G06F11/0781 , G06F11/0775 , G06F11/0778 , G06F11/0787
摘要： Techniques for error report processing are described herein. Error reports, received by a developer due to program crashes, may be organized into a plurality of “buckets.” The buckets may be based in part on a name and a version of the application associated with a crash. Additionally, a call stack of the computer on which the crash occurred may be associated with each error report. The error reports may be “re-bucketed” into meta-buckets to provide additional information to programmers working to resolve software errors. The re-bucketing may be based in part on measuring similarity of call stacks of a plurality of error reports. The similarity of two call stacks—a measure of likelihood that two error reports were caused by a same error—may be based in part on functions in common, a distance of those functions from the crash point, and an offset distance between the common functions.

6. 发明申请

US20150127990A1 Error Report Processing Using Call Stack Similarity 有权
标题翻译：使用调用堆栈相似性的错误报告处理
公开(公告)号：US20150127990A1
公开(公告)日：2015-05-07
申请号：US14594267
申请日：2015-01-12
申请人： Microsoft Technology Licensing, LLC.
发明人： Dongmei Zhang , Yingnong Dang , Song Ge
IPC分类号： G06F11/07
CPC分类号： G06F11/0781 , G06F11/0775 , G06F11/0778 , G06F11/0787
摘要： Techniques for error report processing are described herein. Error reports, received by a developer due to program crashes, may be organized into a plurality of “buckets.” The buckets may be based in part on a name and a version of the application associated with a crash. Additionally, a call stack of the computer on which the crash occurred may be associated with each error report. The error reports may be “re-bucketed” into meta-buckets to provide additional information to programmers working to resolve software errors. The re-bucketing may be based in part on measuring similarity of call stacks of a plurality of error reports. The similarity of two call stacks—a measure of likelihood that two error reports were caused by a same error—may be based in part on functions in common, a distance of those functions from the crash point, and an offset distance between the common functions.
摘要翻译：这里描述了用于错误报告处理的技术。开发人员由于程序崩溃而收到的错误报告可以被组织成多个“桶”。桶可以部分地基于与崩溃相关联的应用的名称和版本。此外，发生崩溃的计算机的调用堆栈可能与每个错误报告相关联。错误报告可能会重新分级到元数据桶中，以便为解决软件错误的程序员提供更多信息。可以部分地基于测量多个错误报告的调用堆栈的相似度来重新估计。两个调用堆栈的相似性 - 两个错误报告由相同错误引起的可能性的度量可能部分地基于共同的功能，这些功能与碰撞点的距离以及公共功能之间的偏移距离。

7. 发明申请

US20190356560A1 QUALITY ASSESSMENT AND DECISION RECOMMENDATION FOR CONTINUOUS DEPLOYMENT OF CLOUD INFRASTRUCTURE COMPONENTS 审中-公开
公开(公告)号：US20190356560A1
公开(公告)日：2019-11-21
申请号：US16516654
申请日：2019-07-19
申请人： Microsoft Technology Licensing, LLC
发明人： Ken Hsieh , Pankaj Kumar Singh , Sree Krishna Chaitanya Vadrevu , Ze Li , Murali Mohan Chintalapati , Yingnong Dang
IPC分类号： H04L12/24 , G06F8/60 , H04L29/08 , G06F9/50 , H04L29/14 , H04L12/26 , G06F11/34
摘要： Methods, systems and computer program products are described for obtaining deployment signals comprising information relating to deployments of software components to a plurality of computing devices, obtaining fault signals comprising information relating to faults encountered by the plurality of computing devices, and obtaining device type information that describes a device type of each of the plurality of computing devices. Based on the deployment signals, fault signals, and device type information, a correlation score for each combination of software component, fault, and device type is obtained. Based on the correlation scores, attribution level decisions, fault type level decisions and device type level decisions are made. Based on these decisions, an overall decision is rendered whether to proceed or not proceed with a future deployment of the software component.

8. 发明申请

US20180307732A1 Frequent pattern mining 审中-公开
公开(公告)号：US20180307732A1
公开(公告)日：2018-10-25
申请号：US15995864
申请日：2018-06-01
申请人： Microsoft Technology Licensing, LLC
发明人： Shi Han , Yingnong Dang , Dongmei Zhang , Song Ge
IPC分类号： G06F17/30 , H04L29/08
CPC分类号： G06F17/30539 , G06F17/30306 , H04L67/10
摘要： A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

9. 发明授权

US11334463B2 Detection of computing resource leakage in cloud computing architectures 有权
公开(公告)号：US11334463B2
公开(公告)日：2022-05-17
申请号：US16321481
申请日：2016-07-29
申请人： Microsoft Technology Licensing, LLC
发明人： Xinsheng Yang , Yingnong Dang , Justin Ding
IPC分类号： G06F11/34 , G06F9/455
摘要： Techniques and systems for detecting leakage of computing resources in cloud computing architectures are described. In some implementations, first data may be obtained that indicates usage of a computing resource, such as non-volatile memory, volatile memory, processor cycles, or network resources, by a group of computing devices included in a cloud computing architecture. The first data may be used to determine reference data that may include a distribution of values of usage of the computing resource by the group of computing devices. Second data may also be collected that indicates usage of the computing resource by the group of computing devices during a subsequent time frame. The second data may be evaluated against the reference data to determine whether one or more conditions indicating a leak of the computing resource are satisfied.

10. 发明授权

US10769007B2 Computing node failure and health prediction for cloud-based data center 有权
公开(公告)号：US10769007B2
公开(公告)日：2020-09-08
申请号：US16003519
申请日：2018-06-08
申请人： Microsoft Technology Licensing, LLC
发明人： Murali M. Chintalapati , Ken Hsieh , Youjiang Wu , Randolph Yao , Qingwei Lin , Yingnong Dang
IPC分类号： G06F11/00 , G06F11/07 , G06N20/00 , G06F9/455 , G06N5/04 , G06N7/00
摘要： A system may include a node historical state data store having historical node state data, including a metric that represents a health status or an attribute of a node during a period of time prior to a node failure. A node failure prediction algorithm creation platform may generate a machine learning trained node failure prediction algorithm. An active node data store may contain information about computing nodes in a cloud computing environment, including, for each node, a metric that represents a health status or an attribute of that node over time. A virtual machine assignment platform may then execute the node failure prediction algorithm to calculate a node failure probability score for each computing node based on the information in the active node data store. As a result, a virtual machine may be assigned to a selected computing node based at least in part on node failure probability scores.

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