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11. 发明授权

US06904433B2 Method for using query templates in directory caches 有权
标题翻译：在目录缓存中使用查询模板的方法
公开(公告)号：US06904433B2
公开(公告)日：2005-06-07
申请号：US09841834
申请日：2001-04-25
申请人： Olga Kapitskaia , Raymond Ng , Divesh Srivastava
发明人： Olga Kapitskaia , Raymond Ng , Divesh Srivastava
IPC分类号： G06F17/30 , H04L9/00 , H04L29/06 , H04L29/08 , H04L29/12
CPC分类号： G06F17/30457 , G06F17/3048 , H04L29/06 , H04L61/1517 , H04L61/1523 , H04L67/2852 , H04L67/289 , Y10S707/99931 , Y10S707/99932 , Y10S707/99933 , Y10S707/99935 , Y10S707/99939 , Y10S707/99953
摘要： The present invention discloses the use of generalized queries, referred to as query templates, obtained by generalizing individual user queries, as the semantic basis for low overhead, high benefit directory caches for handling declarative queries. Caching effectiveness can be improved by maintaining a set of generalizations of queries and admitting such generalizations into the cache when their estimated benefits are sufficiently high. In a preferred embodiment of the invention, the admission of query templates into the cache can be done in what is referred to by the inventors as a “revolutionary” fashion—followed by stable periods where cache admission and replacement can be done incrementally in an evolutionary fashion. The present invention can lead to considerably higher hit rates and lower server-side execution and communication costs than conventional caching of directory queries—while keeping the clientside computational overheads comparable to query caching.
摘要翻译：本发明公开了通过将各个用户查询概括化而获得的通用查询（称为查询模板）作为用于处理声明式查询的低开销，高效益目录高速缓存的语义基础。可以通过维护一组查询的概括来将高速缓存的有效性提高，并且当它们的估计收益足够高时，将这种泛化允许缓存。在本发明的优选实施例中，将查询模板准许到高速缓存中可以在本发明人被称为“革命性”方式的情况下完成 - 其次是稳定的时期，其中缓存允许和替换可以在进化中逐步地完成时尚。与传统的目录查询缓存相比，本发明可以导致相当高的命中率和较低的服务器端执行和通信成本，同时保持客户端计算开销与查询缓存相当。

12. 发明授权

US08943081B2 User-powered recommendation system 有权
标题翻译：用户推荐系统
公开(公告)号：US08943081B2
公开(公告)日：2015-01-27
申请号：US12616892
申请日：2009-11-12
申请人： Kadangode K. Ramakrishnan , Divesh Srivastava , Tae Won Cho , Yin Zhang
发明人： Kadangode K. Ramakrishnan , Divesh Srivastava , Tae Won Cho , Yin Zhang
IPC分类号： G06F17/30 , G11B27/10 , H04N21/475 , H04N21/466
CPC分类号： G06N7/005 , G06F17/30038 , G06F17/30412 , G06F17/3097 , G11B27/105 , H04N21/4661 , H04N21/4668 , H04N21/4756
摘要： Recommendation systems are widely used in Internet applications. In current recommendation systems, users only play a passive role and have limited control over the recommendation generation process. As a result, there is often considerable mismatch between the recommendations made by these systems and the actual user interests, which are fine-grained and constantly evolving. With a user-powered distributed recommendation architecture, individual users can flexibly define fine-grained communities of interest in a declarative fashion and obtain recommendations accurately tailored to their interests by aggregating opinions of users in such communities. By combining a progressive sampling technique with data perturbation methods, the recommendation system is both scalable and privacy-preserving.
摘要翻译：推荐系统广泛应用于互联网应用。在目前的推荐系统中，用户只能发挥被动的作用，对推荐生成过程的控制有限。因此，这些系统提出的建议和实际用户兴趣之间经常存在很大的不匹配，这些建议是细粒度和不断发展的。通过用户分配的推荐体系结构，个人用户可以灵活地定义精细的社区，并以声明方式定义感兴趣的社区，通过汇总用户在这些社区的意见，获得准确定制的兴趣建议。通过将逐行采样技术与数据扰动方法相结合，推荐系统既可扩展又保密。

13. 发明授权

US08645309B2 Processing data using sequential dependencies 有权
标题翻译：使用顺序依赖来处理数据
公开(公告)号：US08645309B2
公开(公告)日：2014-02-04
申请号：US12592586
申请日：2009-11-30
申请人： Lukasz Golab , Howard Karloff , Philip Korn , Divesh Srivastava , Avishek Saha
发明人： Lukasz Golab , Howard Karloff , Philip Korn , Divesh Srivastava , Avishek Saha
IPC分类号： G06F17/00 , G06N7/04 , G06N5/02 , G06N7/00 , G06N7/08 , G06F11/00 , G06F11/30 , G06C25/00 , H03M13/00 , H04L1/00
CPC分类号： G06N7/00 , G06N5/00
摘要： The specification describes data processes for analyzing large data steams for target anomalies. “Sequential dependencies” (SDs) are chosen for ordered data and present a framework for discovering which subsets of the data obey a given sequential dependency. Given an interval G, an SD on attributes X and Y, written as X→G Y, denotes that the distance between the Y-values of any two consecutive records, when sorted on X, are within G. SDs may be extended to Conditional Sequential Dependencies (CSDs), consisting of an underlying SD plus a representation of the subsets of the data that satisfy the SD. The conditional approximate sequential dependencies may be expressed as pattern tableaux, i.e., compact representations of the subsets of the data that satisfy the underlying dependency.
摘要翻译：该规范描述了用于分析目标异常的大型数据流的数据处理。为有序数据选择“顺序依赖”（SDs），并提供一个框架，用于发现数据的哪些子集服从给定的顺序依赖。给定一个间隔G，写入X> GY的属性X和Y上的SD表示当在X上排序时，任何两个连续记录的Y值之间的距离在G之内可以扩展到条件顺序依赖性（CSD）由基础SD加上满足SD的数据子集的表示组成。条件近似顺序依赖性可以表示为模式表，即满足基础依赖性的数据子集的紧凑表示。

14. 发明申请

US20130144843A1 Online Data Fusion 有权
标题翻译：在线数据融合
公开(公告)号：US20130144843A1
公开(公告)日：2013-06-06
申请号：US13311034
申请日：2011-12-05
申请人： Divesh Srivastava , Xin Dong , Xuan Liu
发明人： Divesh Srivastava , Xin Dong , Xuan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/30634
摘要： An online data fusion system receives a query, probes a first source for an answer to the query, returns the answer from the first source, refreshes the answer while probing an additional source, and applies fusion techniques on data associated with an answer that is retrieved from the additional source. For each retrieved answer, the online data fusion system computes the probability that the answer is correct and stops retrieving data for the answer after gaining enough confidence that data retrieved from the unprocessed sources are unlikely to change the answer. The online data fusion system returns correct answers and terminates probing additional sources in an expeditious manner without sacrificing the quality of the answers.
摘要翻译：在线数据融合系统接收查询，探索第一个来源以获得查询的答案，从第一个源返回答案，在探索附加的源时刷新答案，并对与检索到的答案相关联的数据应用融合技术从额外的来源。对于每个检索到的答案，在线数据融合系统计算出答案正确的概率，并且在获得足够的信心从而从未处理的源中检索的数据不太可能改变答案之后，停止检索答案数据。在线数据融合系统返回正确的答案，并以迅速的方式终止探测附加来源，而不牺牲答案的质量。

15. 发明授权

US08295203B2 Methods and systems to store state used to forward multicast traffic 有权
标题翻译：存储用于转发组播流量的状态的方法和系统
公开(公告)号：US08295203B2
公开(公告)日：2012-10-23
申请号：US12060709
申请日：2008-04-01
申请人： Kadangode K. Ramakrishnan , Divesh Srivastava , Tae W. Cho , Yin Zhang , Michael Rabinovich
发明人： Kadangode K. Ramakrishnan , Divesh Srivastava , Tae W. Cho , Yin Zhang , Michael Rabinovich
IPC分类号： H04L12/28
CPC分类号： H04L12/1886 , H04L45/16 , H04L45/48
摘要： Methods and systems are described to store state used to forward multicast traffic. The system includes a receiving module to receive request to add a first node to a membership tree. The membership tree includes a first plurality of nodes associated with a multicast group. The system further includes a processing module to identify a second node in the first plurality of nodes and to communicate a node identifier that identifies the first node over a network to the second node. The node identifier is to be stored at the second node to add the first node to the membership tree. The node identifier is further to be stored in the membership tree exclusively at the second node to enable the second node to forward the multicast traffic to the first node.
摘要翻译：描述了用于存储用于转发组播流量的状态的方法和系统。该系统包括接收模块，用于接收向成员树添加第一个节点的请求。隶属树包括与多播组相关联的第一多个节点。所述系统还包括处理模块，用于识别所述第一多个节点中的第二节点，并将通过网络识别所述第一节点的节点标识符传送到所述第二节点。节点标识符将存储在第二个节点，以将第一个节点添加到成员树中。节点标识符进一步被存储在专属于第二节点的成员树中，以使得第二节点能够将多播业务转发到第一节点。

16. 发明授权

US08161046B2 Selectivity estimation of set similarity selection queries 失效
标题翻译：集合相似性选择查询的选择性估计
公开(公告)号：US08161046B2
公开(公告)日：2012-04-17
申请号：US12274546
申请日：2008-11-20
申请人： Marios Hadjieleftheriou , Nick Koudas , Divesh Srivastava , Xiaohui Yu
发明人： Marios Hadjieleftheriou , Nick Koudas , Divesh Srivastava , Xiaohui Yu
IPC分类号： G06F17/30 , G06F7/00
CPC分类号： G06F17/30469
摘要： The invention relates to a system and/or methodology for selectivity estimation of set similarity queries. More specifically, the invention relates to a selectivity estimation technique employing hashed sampling. The invention providing for samples constructed a priori that can efficiently and quickly provide accurate estimates for arbitrary queries, and can be updated efficiently as well.
摘要翻译：本发明涉及用于组合相似性查询的选择性估计的系统和/或方法。更具体地，本发明涉及采用散列采样的选择性估计技术。本发明提供了可以有效地和快速地为任意查询提供准确估计的先验构建的样本，并且还可以有效地更新。

17. 发明授权

US08145793B1 System and method for distributed content transformation 有权
标题翻译：分布式内容转换的系统和方法
公开(公告)号：US08145793B1
公开(公告)日：2012-03-27
申请号：US10978549
申请日：2004-11-01
申请人： David Gerald Belanger , Steven Michael Bellovin , Maria F. Fernandez , Robert J. Hall , Charles Robert Kalmanek, Jr. , Kathleen McKenna , Divesh Srivastava
发明人： David Gerald Belanger , Steven Michael Bellovin , Maria F. Fernandez , Robert J. Hall , Charles Robert Kalmanek, Jr. , Kathleen McKenna , Divesh Srivastava
IPC分类号： G06F15/16 , G06F15/173
CPC分类号： H04L67/02 , H04L67/10
摘要： A distributed transformation network provides delivery of content from a content publisher to a content recipient. Content from the content publisher is received at an entry node of the distributed transformation network and transmitted to a transformation node in the distributed transformation network. The content is transformed according to publisher, recipient or network administrator specifications and transmitting to delivery nodes which deliver the transformed content to the content recipient. The published content may be in an XML-based format and transformed into an XML-related format or any other structured language format as desired in the provided specification.
摘要翻译：分布式转换网络提供从内容发布者到内容接收者的内容传递。在分布式变换网络的入口节点处接收来自内容发布者的内容，并将其发送到分布式转换网络中的转换节点。内容根据发布者，收件人或网络管理员规范进行转换，并传送到将转换后的内容传递给内容收件人的传送节点。发布的内容可以是基于XML的格式，并且根据所提供的规范中的需要转换成与XML相关的格式或任何其他结构化语言格式。

18. 发明授权

US08103708B2 System and method for generating statistical descriptors for a data stream 有权
标题翻译：用于生成数据流的统计描述符的系统和方法
公开(公告)号：US08103708B2
公开(公告)日：2012-01-24
申请号：US12638140
申请日：2009-12-15
申请人： Graham Cormode , Philip Russell Korn , Shanmugavelayutham Muthukrishnan , Divesh Srivastava
发明人： Graham Cormode , Philip Russell Korn , Shanmugavelayutham Muthukrishnan , Divesh Srivastava
IPC分类号： G06F17/30
CPC分类号： H04L43/026 , H04L41/5003 , H04L41/5009 , H04L41/5029 , Y10S707/913 , Y10S707/99932
摘要： Described is a system and method for receiving a data stream of multi-dimensional items, collecting a sample of the data stream having a predetermined number of items and dividing the sample into a plurality of subsamples, each subsample corresponding to a single dimension of each of the predetermined number of items. A query is then executed on a particular item in at least two of the subsamples to generate data for the corresponding subsample. This data is combined into a single value.
摘要翻译：描述了用于接收多维项目的数据流的系统和方法，收集具有预定数量的项目的数据流的样本并将样本分成多个子样本，每个子样本对应于每个子样本的单个维度预定数量的物品。然后在至少两个子样本中的特定项目上执行查询以生成相应子样本的数据。该数据被组合成单个值。

19. 发明申请

US20110066600A1 FORWARD DECAY TEMPORAL DATA ANALYSIS 有权
标题翻译：前向衰减时间数据分析
公开(公告)号：US20110066600A1
公开(公告)日：2011-03-17
申请号：US12560214
申请日：2009-09-15
申请人： Graham Cormode , Vladislav Shkapenyuk , Divesh Srivastava , Bojian Xu
发明人： Graham Cormode , Vladislav Shkapenyuk , Divesh Srivastava , Bojian Xu
IPC分类号： G06F17/30
CPC分类号： G06F17/30551 , G06F17/30289 , G06F17/30516
摘要： A disclosed method for implementing time decay in the analysis of streaming data objects is based on the age, referred to herein as the forward age, of a data object measured from a landmark time in the past to a time associated with the occurrence of the data object, e.g., an object's timestamp. A forward time decay function is parameterized on the forward age. Because a data object's forward age does not depend on the current time, a value of the forward time decay function is determined just once for each data object. A scaling factor or weight associated with a data object may be weighted according to its decay function value. Forward time decay functions are beneficial in determining decayed aggregates, including decayed counts, sums, and averages, decayed minimums and maximums, and for drawing decay-influenced samples.
摘要翻译：用于在流数据对象的分析中实现时间衰减的公开方法基于从过去的地标时间测量到与数据的出现相关联的时间的数据对象的年龄（这里称为远期时间）对象，例如对象的时间戳。前进时间衰减函数在前进时间参数化。因为数据对象的转发时间不依赖于当前时间，因此对于每个数据对象仅确定一次正向时间衰减函数的值。可以根据其衰减函数值对与数据对象相关联的缩放因子或权重进行加权。前向时间衰减函数有助于确定衰变的聚集体，包括衰变计数，总和和平均值，衰减最小值和最大值，以及绘制衰变影响样本。

20. 发明申请

US20100125559A1 SELECTIVITY ESTIMATION OF SET SIMILARITY SELECTION QUERIES 失效
标题翻译：选择性相似性选择问题的选择性估计
公开(公告)号：US20100125559A1
公开(公告)日：2010-05-20
申请号：US12274546
申请日：2008-11-20
申请人： Marios Hadjieleftheriou , Nick Koudas , Divesh Srivastava , Xiaohui Yu
发明人： Marios Hadjieleftheriou , Nick Koudas , Divesh Srivastava , Xiaohui Yu
IPC分类号： G06F7/06 , G06F17/30
CPC分类号： G06F17/30469
摘要： The invention relates to a system and/or methodology for selectivity estimation of set similarity queries. More specifically, the invention relates to a selectivity estimation technique employing hashed sampling. The invention providing for samples constructed a priori that can efficiently and quickly provide accurate estimates for arbitrary queries, and can be updated efficiently as well.
摘要翻译：本发明涉及用于组合相似性查询的选择性估计的系统和/或方法。更具体地，本发明涉及采用散列采样的选择性估计技术。本发明提供了可以有效地和快速地为任意查询提供准确估计的先验构建的样本，并且还可以有效地更新。

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