Selective, contextual review for documents
    1.
    发明申请
    Selective, contextual review for documents 审中-公开
    文件的选择性,背景审查

    公开(公告)号:US20070260588A1

    公开(公告)日:2007-11-08

    申请号:US11430709

    申请日:2006-05-08

    IPC分类号: G06F17/30

    CPC分类号: G06F16/3338 G06F16/3344

    摘要: A method, apparatus and computer-usable medium for the selective, contextual retrieval and presentation of information used in review processes. Search criteria is entered for information to be retrieved for review and information source documents are then searched, maintaining references to the contextual levels encountered (e.g., chapter, section, sub-section, etc.). Once the search is completed, a hierarchical list of sentence extracts matching the search criteria and indicating their location in their respective source document is presented to the reviewer. The user can then select any level of the hierarchical view, which then displays an expanded view of the related section of the source document. The retrieved information can be exported to a plurality of formats, which are annotatable by the reviewer. Users are thereby provided with information relevant to the subject under review, structured and presented in the context of its usage within its associated source document.

    摘要翻译: 用于在审查过程中使用的信息的选择性,上下文检索和呈现的方法,装置和计算机可用介质。 输入要检索的信息以进行审查的搜索标准,然后搜索信息源文档,保持对遇到的上下文级别(例如,章节,部分,子部分等)的引用。 一旦搜索完成,就将与搜索条件匹配的句子提取的分层列表以及它们各自的源文档中的位置提供给审阅者。 然后,用户可以选择任何级别的分层视图,然后显示源文档的相关部分的扩展视图。 检索到的信息可以被导出为多个格式,这些格式可由审阅者注释。 从而向用户提供与被审查对象有关的信息,在其相关源文档中的使用情况下进行结构化和呈现。

    Cross-cutting event correlation
    3.
    发明申请
    Cross-cutting event correlation 有权
    横切事件相关

    公开(公告)号:US20070233836A1

    公开(公告)日:2007-10-04

    申请号:US11395736

    申请日:2006-03-31

    IPC分类号: G06F15/173

    摘要: Embodiments of the present invention provide a method, system and computer program product for cross-cutting event correlation in an enterprise computing monitoring and management system. An enterprise computing monitoring and management system can include a hierarchy of nodes, where several of the nodes are each coupled to a corresponding embedded correlation engine and an event bus. The system further can include a root node among the nodes. The root node can be coupled to the event bus and to centralized correlation logic programmed to identify a high correspondence between events from a particular event source among the nodes and a particular set of correlation rules in that correlation engine. The identification of such correspondence can be used to move to the set of correlation rules to an embedded correlation engine closer to the particular event source.

    摘要翻译: 本发明的实施例提供了一种用于企业计算监控和管理系统中交叉事件相关性的方法,系统和计算机程序产品。 企业计算监视和管理系统可以包括节点层级,其中几个节点各自耦合到相应的嵌入式相关引擎和事件总线。 该系统还可以包括节点之间的根节点。 根节点可以耦合到事件总线,并且集中相关逻辑被编程以识别来自节点之间的特定事件源的事件与该相关引擎中的一组特定相关规则之间的高对应关系。 这种对应关系的识别可以用于将一组相关性规则移动到更靠近特定事件源的嵌入式相关引擎。

    Predictive help method, system and program product for software systems
    5.
    发明申请
    Predictive help method, system and program product for software systems 审中-公开
    软件系统的预测性帮助方法,系统和程序产品

    公开(公告)号:US20060036991A1

    公开(公告)日:2006-02-16

    申请号:US10916651

    申请日:2004-08-12

    IPC分类号: G06F9/44

    CPC分类号: G06F9/453

    摘要: Under the present invention, a sequence of actions made by a user in operating a software system is tracked. Upon request by the user, predictive help is given based on the sequence of actions. In a typical embodiment, the predictive help is contained in a knowledge base, which is initially built during development of the software system. Specifically, the knowledge base is populated based on sequences of actions by other users as they operate the software system during its development. Moreover, the knowledge base can be updated after release of the software system as the user operates the system. To this extent, the knowledge base will “learn” the patterns of the user, and the predictive help will be continually tailored based thereon.

    摘要翻译: 在本发明中,跟踪用户在操作软件系统中所做的一系列动作。 根据用户的要求,基于动作顺序给出预测性帮助。 在典型的实施例中,预测性帮助包含在知识库中,知识库最初是在软件系统的开发过程中构建的。 具体来说,知识库在其开发过程中操作软件系统时,基于其他用户的动作顺序进行填充。 而且,随着用户操作系统,知识库可以在软件系统释放之后被更新。 在这种程度上,知识库将“学习”用户的模式,并且将基于此来不断地定制预测性帮助。