Network-based filtering for large email collections in E-Discovery

Artificial Intelligence and Law 18 (4):413-430 (2010)

Abstract
The information overload in E-Discovery proceedings makes reviewing expensive and it increases the risk of failure to produce results on time and consistently. New interactive techniques have been introduced to increase reviewer productivity. In contrast, the techniques presented in this article propose an alternative method that tries to reduce information during culling so that less information needs to be reviewed. The proposed method first focuses on mapping the email collection universe using straightforward statistical methods based on keyword filtering combined with date time and custodian identities. Subsequently, a social network is constructed from the email collection that is analyzed by filtering on date time and keywords. By using the network context we expect to provide a better understanding of the keyword hits and the ability to discard certain parts of the collection
Keywords E-Discovery  Social network analysis  Information retrieval  Email visualisation
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DOI 10.1007/s10506-010-9099-3
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