A Query Recommending Scheme for an efficient evidence search in e-Discovery

In recent years, the importance of e-Discovery is being strongly emphasized according to the rapid increase of litigation between the business corporations. The success of e-Discovery depends on how well the litigant and lawyer search relevant evidence, and it is closely associated with making fine queries based on their analysis of complaint and data set. Therefore, this paper proposes a Query Recommending Scheme called QRS for an efficient evidence search in e-Discovery procedure. This scheme is composed with four different phases and various techniques are applied such as document parsing, machine learning and scoring. We describe how QRS works using the flow chart and introduce further researches for the improvement of QRS.