TY - CHAP

T1 - Scaling out to become doctrinal

AU - Panagis, Yannis

AU - Sakkopoulos, Evangelos

PY - 2017/1/1

Y1 - 2017/1/1

N2 - International courts are often prolific and produce a huge amount of decisions per year which makes it extremely difficult both for researchers and practitioners to follow. It would be thus convenient for the legal researchers to be given the ability to get an idea of the topics that are dealt with in the judgments produced by the courts, without having to read through the judgments. This is exactly a use case for topic modeling, however, the volume of data is such that calls for an out-of-core solution. In this paper we are experimenting in this direction by using the data from two major, large international courts.We thus, experiment with topic modeling in Big Data architectures backed by a MapReduce framework. We demonstrate both the feasibility of our approach and the accuracy of the produced topic models that manage to outline very well the development of the subject matters of the courts under study.

AB - International courts are often prolific and produce a huge amount of decisions per year which makes it extremely difficult both for researchers and practitioners to follow. It would be thus convenient for the legal researchers to be given the ability to get an idea of the topics that are dealt with in the judgments produced by the courts, without having to read through the judgments. This is exactly a use case for topic modeling, however, the volume of data is such that calls for an out-of-core solution. In this paper we are experimenting in this direction by using the data from two major, large international courts.We thus, experiment with topic modeling in Big Data architectures backed by a MapReduce framework. We demonstrate both the feasibility of our approach and the accuracy of the produced topic models that manage to outline very well the development of the subject matters of the courts under study.

KW - Big Data

KW - European Court of Human Rights

KW - European Court of Justice

KW - Latent Dirichlet Allocation

KW - MapReduce

UR - http://www.scopus.com/inward/record.url?scp=85018711034&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-57045-7_10

DO - 10.1007/978-3-319-57045-7_10

M3 - Book chapter

AN - SCOPUS:85018711034

SN - 9783319570440

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 157

EP - 168

BT - Algorithmic Aspects of Cloud Computing - 2nd International Workshop,ALGOCLOUD 2016, Revised Selected Papers

PB - Springer Verlag,

T2 - 2nd International Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2016

Y2 - 22 August 2016 through 22 August 2016

ER -