通过邮件联系网络识别可能涉及特权通信的文档。
Detecting Privileged Documents by Ranking Connected Network Entities
- 基于邮件头构建人物关联网络，区分律师与非律师
- 结合个体评分与连接强度，提升特权文档识别率
- 适合法律取证与电子证据分析场景
本文提出一种链接分析方法，通过电子邮件头元数据构建人物关联网络，将实体分类为律师或非律师。核心假设是：频繁与律师互动的个体更可能参与特权通信。算法为网络中每个实体分配评分，结合评分与连接强度，增强对特权文档的识别能力。实验结果表明该方法在排序法律相关实体以检测特权文档方面具有有效性。
原文摘要 · Abstract (English)
This paper presents a link analysis approach for identifying privileged documents by constructing a network of human entities derived from email header metadata. Entities are classified as either counsel or non-counsel based on a predefined list of known legal professionals. The core assumption is that individuals with frequent interactions with lawyers are more likely to participate in privileged communications. To quantify this likelihood, an algorithm assigns a score to each entity within the network. By utilizing both entity scores and the strength of their connections, the method enhances the identification of privileged documents. Experimental results demonstrate the algorithm's effectiveness in ranking legal entities for privileged document detection.
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