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    • 5. 发明申请
    • CONTEXT BASED ACCESS PATH SELECTION
    • 基于上下文的访问路径选择
    • US20170075957A1
    • 2017-03-16
    • US15345168
    • 2016-11-07
    • International Business Machines Corporation
    • Shuo LiLi YangKe Wei WeiXin Ying YangJian Wei Zhang
    • G06F17/30
    • G06F17/30469G06F17/30474G06F17/30516
    • A computer-implemented method includes receiving a batch processing job. The method identifies multiple access paths for the batch processing job. The method determines one or more runtime costs for each of the multiple access paths. The method determines whether the batch processing job includes comparable access paths. The method responds to the batch processing job not including comparable access paths by receiving a query and selecting a desired access, based on the one or more runtime costs. The method responds to the batch processing job including comparable access paths by determining one or more context costs for each of the one or more access paths, receiving a query, identifying a context for the query, and selecting a desired access path for the query. The desired access path is based on the one or more runtime costs, the one or more context costs, and the context for the query.
    • 计算机实现的方法包括接收批处理作业。 该方法识别批处理作业的多个访问路径。 该方法确定多个访问路径中的每一个的一个或多个运行时间成本。 该方法确定批处理作业是否包括可比较的访问路径。 该方法通过基于一个或多个运行时间费用接收查询和选择所需的访问来响应不包括可比较的访问路径的批处理作业。 该方法通过为一个或多个访问路径中的每一个确定一个或多个上下文成本,接收查询,标识查询的上下文以及为查询选择所需的访问路径来响应批量处理作业,包括可比较的访问路径。 期望的访问路径基于一个或多个运行时成本,一个或多个上下文成本以及查询的上下文。
    • 9. 发明授权
    • User interface for predictive model generation
    • 用于预测模型生成的用户界面
    • US09251203B2
    • 2016-02-02
    • US14136386
    • 2013-12-20
    • MModal IP LLC
    • Jonathan A. HandlerJuergen Fritsch
    • G06F17/30G06F17/18
    • G06F17/30554G06F17/18G06F17/30345G06F17/30424G06F17/30474G06F17/30477G06N7/005
    • A dataset is searched using inclusion set criteria to produce an inclusion set and exclusion set criteria to produce an exclusion set. A set of unique content elements is identified from the inclusion set and the exclusion set. Metrics are derived from the inclusion set, exclusion set, and set of unique content elements, such as a measure, for each unique content element, of the absolute value of the difference between the percentage of records in the inclusion set containing the unique content element and the percentage of records in the exclusion set containing the unique content element. The unique content element set may be sorted and displayed in decreasing order of the above-referenced absolute value. The content element set may be filtered. Individual content elements may be excluded from the content set. A predictive model may be generated based on the resulting version of the content element set.
    • 使用包含集合标准搜索数据集以生成包含集和排除集合标准以生成排除集合。 从包含集合和排除集合中识别一组唯一的内容元素。 度量是从包含集合,排除集合和唯一内容元素集合(例如每个唯一内容元素的度量)导出包含唯一内容元素的包含集合中记录的百分比之间的差异的绝对值 以及包含唯一内容元素的排除集中的记录百分比。 可以按照上述绝对值的递减顺序对独特的内容元素集合进行排序和显示。 内容元素集可以被过滤。 可以从内容集中排除各个内容元素。 可以基于所生成的内容元素集的版本来生成预测模型。