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

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 research that is discussed in this paper proposes 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.

• Type: Journal
• Year: 2010
• Where: AIL
• Authors: Hans Henseler
• Keywords: AIL 2010, Artificial Intelligence, Date Time, Email Collection, Straightforward Statistical Methods