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

US20100325132A1 QUERYING COMPRESSED TIME-SERIES SIGNALS 有权
标题翻译：查询压缩时间序列信号
公开(公告)号：US20100325132A1
公开(公告)日：2010-12-23
申请号：US12488598
申请日：2009-06-22
申请人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
发明人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
IPC分类号： G06F17/30
CPC分类号： G06F17/30516
摘要： A system described herein includes a receiver component that receives a query that pertains to a raw time-series signal. A query executor component selectively executes the query over at least one of multiple available compressed representations of the raw time-series signal, wherein the query pertains to at least one of one of determining a trend pertaining to the raw time-series signal, generating a histogram pertaining to the raw time-series signal, or determining a correlation pertaining to the raw time-series signal.
摘要翻译：本文描述的系统包括接收与原始时间序列信号有关的查询的接收器组件。查询执行器组件通过原始时间序列信号的多个可用压缩表示中的至少一个选择性地执行查询，其中查询涉及确定与原始时间序列信号有关的趋势中的至少一个，生成关于原始时间序列信号的直方图，或者确定与原始时间序列信号有关的相关性。

2. 发明申请

US20090222544A1 FRAMEWORK FOR JOINT ANALYSIS AND DESIGN OF SERVER PROVISIONING AND LOAD DISPATCHING FOR CONNECTION-INTENSIVE SERVER 有权
标题翻译：用于连接强度服务器的服务器提供和负载分配的联合分析和设计框架
公开(公告)号：US20090222544A1
公开(公告)日：2009-09-03
申请号：US12041478
申请日：2008-03-03
申请人： Lin Xiao , Jie Liu , Suman Kumar Nath , Leonidas Rigas , Feng Zhao , Gong Chen , Wenbo He
发明人： Lin Xiao , Jie Liu , Suman Kumar Nath , Leonidas Rigas , Feng Zhao , Gong Chen , Wenbo He
IPC分类号： G06F15/16
CPC分类号： H04L41/5054 , H04L41/0806 , H04L41/147 , H04L67/1002
摘要： The claimed subject matter provides a system and/or a method that facilitates managing a number of active servers in a cluster. A forecast component can predict at least one of login rate or number of connections in the cluster at a future time. A dynamic load analysis component can evaluate dynamic behaviors in login rate and number of connections in the cluster as a result of load dispatching. Moreover, a provisioning component can determine a number of servers in the cluster needed based at least in part on the prediction and dynamic behavior analysis. In addition, the provisioning component can include an additional margin in the number of servers needed in accordance with multiplicative factors.
摘要翻译：所要求保护的主题提供了有助于管理群集中的多个活动服务器的系统和/或方法。预测组件可以在将来的时间预测群集中的登录速率或连接数中的至少一个。动态负载分析组件可以通过负载调度来评估集群中登录速率和连接数的动态行为。此外，配置组件可以至少部分地基于预测和动态行为分析来确定所需的群集中的服务器数量。此外，配置组件可以包括根据乘法因子所需的服务器数量的额外余量。

3. 发明授权

US08655887B2 Querying compressed time-series signals 有权
标题翻译：查询压缩时间序列信号
公开(公告)号：US08655887B2
公开(公告)日：2014-02-18
申请号：US13491838
申请日：2012-06-08
申请人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
发明人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30516
摘要： Technologies pertaining to compressing time-series signals are described herein. Groups of time-series signals are generated based upon similarities between time-series signals. Each group of time-series signals includes a respective base time-series signal. Ratio signals that are representative of time-series signals are computed, wherein the ratio signals are based upon the base time-series signal and other respective time-series signals in a group of time-series signals.
摘要翻译：本文描述了压缩时间序列信号的技术。基于时间序列信号之间的相似度生成时间序列信号组。每组时间序列信号包括各自的基本时间序列信号。计算代表时间序列信号的比率信号，其中比率信号基于一组时间序列信号中的基本时间序列信号和其它相应的时间序列信号。

4. 发明申请

US20130332442A1 DEEP APPLICATION CRAWLING 有权
标题翻译： DEEP应用程序CRAWLING
公开(公告)号：US20130332442A1
公开(公告)日：2013-12-12
申请号：US13490335
申请日：2012-06-06
申请人： Jie Liu , Suman Kumar Nath , Jitendra D. Padhye , Lenin Ravindranath Sivalingam
发明人： Jie Liu , Suman Kumar Nath , Jitendra D. Padhye , Lenin Ravindranath Sivalingam
IPC分类号： G06F17/30
CPC分类号： G06Q30/0256 , G06F17/30864 , G06F17/30882 , G06Q30/0267
摘要： The deep application crawling technique described herein crawls one or more applications, commonly referred to as “apps”, in order to extract information inside of them. This can involve crawling and extracting static data that are embedded within apps or resource files that are associated with the apps. The technique can also crawl and extract dynamic data that apps download from the Internet or display to the user on demand, in order to extract data. This extracted static and/or data can then be used by another application or an engine to perform various functions. For example, the technique can use the extracted data to provide search results in response to a user query entered into a search engine. Alternately, the extracted static and/or dynamic data can be used by an advertisement engine to select application-specific advertisements. Or the data can be used by a recommendation engine to make recommendations for goods/services.
摘要翻译：本文描述的深层应用程序爬取技术抓取一个或多个应用程序，通常称为“应用程序”，以便提取其中的信息。这可能涉及爬网和提取内嵌在与应用程序相关联的应用程序或资源文件中的静态数据。该技术还可以抓取并提取应用程序从Internet下载或按需显示的动态数据，以便提取数据。然后，该提取的静态和/或数据可以被另一应用或引擎用于执行各种功能。例如，该技术可以使用提取的数据来响应输入到搜索引擎中的用户查询来提供搜索结果。或者，所提取的静态和/或动态数据可以由广告引擎用于选择特定应用的广告。或者推荐引擎可以使用数据来提供商品/服务的建议。

5. 发明申请

US20120246169A1 QUERYING COMPRESSED TIME-SERIES SIGNALS 有权
标题翻译：查询压缩时间序列信号
公开(公告)号：US20120246169A1
公开(公告)日：2012-09-27
申请号：US13491838
申请日：2012-06-08
申请人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
发明人： Jie Liu , Suman Kumar Nath , Feng Zhao , Galen Andrew Reeves , Sorabh Kumar Gandhi
IPC分类号： G06F17/30 , G06F7/00
CPC分类号： G06F17/30516
摘要： Technologies pertaining to compressing time-series signals are described herein. Groups of time-series signals are generated based upon similarities between time-series signals. Each group of time-series signals includes a respective base time-series signal. Ratio signals that are representative of time-series signals are computed, wherein the ratio signals are based upon the base time-series signal and other respective time-series signals in a group of time-series signals.
摘要翻译：本文描述了压缩时间序列信号的技术。基于时间序列信号之间的相似度生成时间序列信号组。每组时间序列信号包括各自的基本时间序列信号。计算代表时间序列信号的比率信号，其中比率信号基于一组时间序列信号中的基本时间序列信号和其它相应的时间序列信号。

6. 发明申请

US20120110015A1 SEARCH CACHE FOR DOCUMENT SEARCH 有权
标题翻译：搜索缓存文件搜索
公开(公告)号：US20120110015A1
公开(公告)日：2012-05-03
申请号：US12915045
申请日：2010-10-29
申请人： Suman Kumar Nath , Pavan Kumar Athivarapu
发明人： Suman Kumar Nath , Pavan Kumar Athivarapu
IPC分类号： G06F17/30
CPC分类号： G06F17/30864 , G06F17/30693 , G06F17/30902
摘要： A method is described herein that includes receiving a query from a user at a computing device. The method also includes performing a search for one or more documents based at least in part upon the received query, wherein performing the search comprises causing a processor to perform the search through utilization of a search cache retained on the computing device, wherein the search cache comprises a results cache, an index cache, and a Boolean cache.
摘要翻译：这里描述了一种方法，其包括在计算设备处从用户接收查询。所述方法还包括至少部分地基于所接收的查询来执行对一个或多个文档的搜索，其中执行所述搜索包括使处理器通过使用所述计算设备上保留的搜索高速缓存来执行搜索，其中所述搜索高速缓存包括结果缓存，索引缓存和布尔高速缓存。

7. 发明申请

US20100030809A1 MAINTAINING LARGE RANDOM SAMPLE WITH SEMI-RANDOM APPEND-ONLY OPERATIONS 有权
标题翻译：维持随机附带的大量随机样本
公开(公告)号：US20100030809A1
公开(公告)日：2010-02-04
申请号：US12184213
申请日：2008-07-31
申请人： Suman Kumar Nath
发明人： Suman Kumar Nath
IPC分类号： G06F17/30
CPC分类号： G11C11/5621
摘要： Systems and methods are provided for online maintenance, processing, and querying of large random samples of data from a large/infinite data stream. In an illustrative implementation an exemplary computing environment comprises at least one data store, a data storage and management engine operable to process and/or store data according to a selected data processing and storage management paradigm on a cooperating data store (e.g., flash media). The exemplary data storage and management engine can deploy the exemplary sampling algorithm to perform and/or provide one or more of the following operations/features comprising the algorithm is operable for streaming data (or a single pass through the dataset), allows for the semi-random data write operations, the algorithm avoids operations (e.g., in-place updates) that are expensive on flash storage media, and the algorithm is tunable to both the amount of flash storage and the amount of standard memory (DRAM) available to the algorithm.
摘要翻译：提供系统和方法用于在大型/无限数据流中在线维护，处理和查询大量随机数据样本。在说明性实现中，示例性计算环境包括至少一个数据存储器，数据存储和管理引擎，可操作以根据在协作数据存储器（例如，闪存介质）上的所选数据处理和存储管理范例来处理和/或存储数据，。示例性数据存储和管理引擎可以部署示例性采样算法来执行和/或提供以下操作/特征中的一个或多个，其包括该算法可操作用于流数据（或单次通过数据集），允许半 - 随机数据写入操作，该算法避免了在闪存存储介质上昂贵的操作（例如，就地更新），并且该算法可调整到闪存存储量和可用于闪存存储器的标准存储器（DRAM）的数量算法。

8. 发明申请

US20090144011A1 ONE-PASS SAMPLING OF HIERARCHICALLY ORGANIZED SENSORS 有权
标题翻译：一次性采样分层组织传感器
公开(公告)号：US20090144011A1
公开(公告)日：2009-06-04
申请号：US11948667
申请日：2007-11-30
申请人： Suman Kumar Nath
发明人： Suman Kumar Nath
IPC分类号： G01C25/00
CPC分类号： G01C25/00
摘要： One-pass sampling is employed within a hierarchically organized structure to efficiently and expeditiously respond to sensor inquires. Identification of relevant sensors and sampling of those sensors is combined and performed in a single pass. Oversampling can also be employed to ensure a target sample size is met where some sensors fail or are otherwise unavailable. Further yet, sensor data can be cached and utilized to hasten processing as well as compensate for occasional sensor unavailability.
摘要翻译：在分层组织的结构中采用单程采样，以有效和快速地响应传感器查询。相关传感器的识别和这些传感器的采样在单程中组合并执行。也可以采用过采样来确保在某些传感器出现故障或不可用的情况下满足目标样本大小。此外，传感器数据可以被缓存并用于加速处理以及补偿偶尔的传感器不可用性。

9. 发明授权

US08805833B2 Enhancing personal data search with information from social networks 有权
标题翻译：通过社交网络的信息增强个人数据搜索
公开(公告)号：US08805833B2
公开(公告)日：2014-08-12
申请号：US12954247
申请日：2010-11-24
申请人： Suman Kumar Nath , Douglas Christopher Burger
发明人： Suman Kumar Nath , Douglas Christopher Burger
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06Q30/0282 , G06Q50/01
摘要： The personal data search technique uses data input by users for a given user's personal data on a social networking site to enrich the given user's personal data. The technique annotates personal data stored on a personal computing device or in a computing cloud with data obtained from social networking sites (for example, tags, comments, likes/dislikes and so forth) provided by friends/other users in the given user's social network or networks. Such annotations can later are used by search engine to enhance the search functionality and/or to improve the ranking of search results. Since the data is entered by actual human users it is very accurate and since the data is already readily available on social networks the cost to obtain it is very inexpensive.
摘要翻译：个人数据搜索技术使用用户在社交网站上给定用户的个人数据输入的数据，以丰富给定用户的个人数据。该技术使用从给定用户的社交网络中的朋友/其他用户提供的社交网站（例如，标签，评论，喜欢/不喜欢等）获得的数据来注释存储在个人计算设备或计算云中的个人数据或网络。这样的注释可以稍后被搜索引擎用来增强搜索功能和/或提高搜索结果的排名。由于数据是由实际的人类用户输入的，因此这是非常准确的，由于数据已经在社交网络上已经很容易获得，因此获得成本非常便宜。

10. 发明授权

US08352519B2 Maintaining large random sample with semi-random append-only operations 有权
标题翻译：通过半随机附加操作维护大量随机样本
公开(公告)号：US08352519B2
公开(公告)日：2013-01-08
申请号：US12184213
申请日：2008-07-31
申请人： Suman Kumar Nath
发明人： Suman Kumar Nath
IPC分类号： G06F17/30
CPC分类号： G11C11/5621
摘要： Systems and methods are provided for online maintenance, processing, and querying of large random samples of data from a large/infinite data stream. In an illustrative implementation an exemplary computing environment comprises at least one data store, a data storage and management engine operable to process and/or store data according to a selected data processing and storage management paradigm on a cooperating data store (e.g., flash media). The exemplary data storage and management engine can deploy the exemplary sampling algorithm to perform and/or provide one or more of the following operations/features comprising the algorithm is operable for streaming data (or a single pass through the dataset), allows for the semi-random data write operations, the algorithm avoids operations (e.g., in-place updates) that are expensive on flash storage media, and the algorithm is tunable to both the amount of flash storage and the amount of standard memory (DRAM) available to the algorithm.
摘要翻译：提供系统和方法用于在大型/无限数据流中在线维护，处理和查询大量随机数据样本。在说明性实现中，示例性计算环境包括至少一个数据存储器，数据存储和管理引擎，可操作以根据在协作数据存储器（例如，闪存介质）上的所选数据处理和存储管理范例来处理和/或存储数据，。示例性数据存储和管理引擎可以部署示例性采样算法来执行和/或提供以下操作/特征中的一个或多个，其包括该算法可操作用于流数据（或单次通过数据集），允许半 - 随机数据写入操作，该算法避免了在闪存存储介质上昂贵的操作（例如，就地更新），并且该算法可调整到闪存存储量和可用于闪存存储器的标准存储器（DRAM）的数量算法。

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