Title :
A Query Recommending Scheme for an efficient evidence search in e-Discovery
Author :
Heon-Min Lee ; Su-bin Han ; Taerim Lee ; Sang Uk Shin
Author_Institution :
Dept. of Inf. Security the Grad. Sch., Pukyong Nat. Univ., Busan, South Korea
Abstract :
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.
Keywords :
document handling; law administration; learning (artificial intelligence); query processing; recommender systems; QRS; business corporations; document parsing; e-discovery; evidence search; fine queries; flow chart; lawyer; litigation; machine learning; query recommending scheme; relevant evidence; Data mining; Digital forensics; Educational institutions; Information security; Patents; Electronic Discovery; Evidence Search; Machine Learning; Query Recommending; e-Discovery;
Conference_Titel :
Advanced Communication Technology (ICACT), 2014 16th International Conference on
Conference_Location :
Pyeongchang
Print_ISBN :
978-89-968650-2-5
DOI :
10.1109/ICACT.2014.6779156
