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公开(公告)号：WO2015030720A1
公开(公告)日：2015-03-05
申请号：PCT/US2013/056722
申请日：2013-08-27
Applicant: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
Inventor： LIU, Lian , GUPTA, Chetan Kumar , VISWANATHAN, Krishnamurthy
IPC: G01C21/34 , G08G1/0969
CPC classification number: G01C21/34 , G01C21/3492 , G08G1/096811 , G08G1/096844 , G08G1/096888
Abstract: Disclosed herein are a system, non-transitory computer readable medium, and method to handle a routing problem. It is determined whether a fastest route can be resolved using static routing or time dependent routing.
Abstract translation: 本文公开了一种用于处理路由问题的系统，非暂时计算机可读介质和方法。 确定是否可以使用静态路由或时间相关路由来解决最快的路由。
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公开(公告)号：WO2012054022A1
公开(公告)日：2012-04-26
申请号：PCT/US2010/053222
申请日：2010-10-19
Inventor： DEKHIL, Mohamed E. , GUPTA, Chetan Kumar
CPC classification number: G06F17/218 , G06Q10/10 , G06Q30/02
Abstract: The present disclosure provides a computer-implemented method (300) of managing content from structured and unstructured data sources. The method (300) includes adding a first item to an information management project, wherein the first item includes unstructured content selected from an unstructured data source and a data link corresponding to the unstructured content (304). The method (300) also includes adding a second item to the information management project, wherein the second item includes a database query and structured data corresponding to the database query (306). The method (300) also includes generating a presentation document based on the information management project, the presentation document comprising the unstructured content and the structured data (308).
Abstract translation: 本公开提供了一种从结构化和非结构化数据源管理内容的计算机实现的方法（300）。 方法（300）包括将第一项目添加到信息管理项目，其中第一项目包括从非结构化数据源和对应于非结构化内容的数据链路选择的非结构化内容（304）。 方法（300）还包括向信息管理项目添加第二项目，其中第二项目包括对应于数据库查询的数据库查询和结构化数据（306）。 所述方法（300）还包括基于所述信息管理项目生成呈现文档，所述呈现文档包括所述非结构化内容和所述结构化数据（308）。
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公开(公告)号：WO2015038152A1
公开(公告)日：2015-03-19
申请号：PCT/US2013/059837
申请日：2013-09-14
Applicant: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
Inventor： CHERKASOVA, Ludmila , GUPTA, Chetan Kumar , SIMITSIS, Alkiviadis , WANG, Jianqiang , WILKINSON, William K
CPC classification number: G06N5/04 , G06F17/30445 , G06N99/005
Abstract: Example embodiments relate to predicting execution times of concurrent queries. In example embodiments, historical data is iteratively generated for a machine learning model by varying a concurrency level of query executions in a database, determining a query execution plan for a pending concurrent query, extracting query features from the query execution plan, and executing the pending concurrent query to determine a query execution time. The machine learning model may then be created based on the query features, variation in the concurrency level, and the query execution time. The machine learning model is used to generate an execution schedule for production queries, where the execution schedule satisfies service level agreements of the production queries.
Abstract translation: 示例实施例涉及预测并发查询的执行时间。 在示例实施例中，通过改变数据库中的查询执行的并发级别，确定待执行的并发查询的查询执行计划，从查询执行计划中提取查询特征以及执行待处理的查询执行计划，迭代地为机器学习模型生成历史数据 并发查询确定查询执行时间。 然后可以基于查询特征，并发级别的变化和查询执行时间来创建机器学习模型。 机器学习模型用于生成生产查询的执行计划，其中执行计划满足生产查询的服务级别协议。
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公开(公告)号：WO2014065804A1
公开(公告)日：2014-05-01
申请号：PCT/US2012/061935
申请日：2012-10-25
Applicant: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
IPC: G06F9/44
CPC classification number: G06F9/542 , G06F9/448 , G06F11/008 , G06F2201/86
Abstract: A method for event correlation includes capturing events and arranging the events sequentially in at least one dimension. An event correlator implemented by a computational device convolves a kernel density function with each of the events to produce a convolved function for each event. Co-occurrences between events are found by calculating overlap between convolved functions.
Abstract translation: 用于事件相关的方法包括捕获事件并且在至少一个维度中顺序排列事件。 由计算设备实现的事件相关器将核心密度函数与每个事件相结合，以产生每个事件的卷积函数。 通过计算卷积函数之间的重叠来发现事件之间的共同事件。
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