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DATA CLASSIFICATION USING DATA FLOW ANALYSIS

机译:使用数据流分析进行数据分类

摘要

Described herein is a system and method for utilizing data flow analysis to perform data classification with respect to a source dataset and a generated derived dataset. A flow confidence for a field is calculated using an adaptive algorithm in accordance with the action performed and the derived dataset. An associated derived confidence for a particular tag is calculated in accordance with an associated confidence and the flow confidence. When the associated derived confidence is greater than or equal to a first threshold, the particular tag is copied to the derived dataset. In some embodiments, when the associated derived confidence is less than or equal to a second threshold, the particular tag is not copied to the derived dataset. Otherwise an action to be taken is identified. A response to the action is received and the adaptive algorithm is modified in accordance with the received response.
机译:本文描述了一种用于利用数据流分析来针对源数据集和所生成的派生数据集进行数据分类的系统和方法。根据执行的操作和派生的数据集,使用自适应算法来计算字段的流量置信度。根据相关联的置信度和流置信度计算特定标签的相关联的导出置信度。当相关联的导出置信度大于或等于第一阈值时,将特定标签复制到导出数据集。在一些实施例中,当相关联的导出置信度小于或等于第二阈值时,特定标签不被复制到导出数据集。否则,确定要采取的措施。接收对动作的响应,并且根据所接收的响应来修改自适应算法。

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