A Big Data Analytics Platform for Information Sharing in the Connection Between Administrative Law and Criminal Justice

Big data analysis and application is an efficient approach for analyzing and identifying different patterns, relations and trends in daily life. In this paper we proposed an intelligent big data platform for information sharing in connection to administrative law and criminal justice. We first explored the structure of the data and utilized Apache Pig and Hadoop to handle structured, semi-structured and unstructured data. We extracted and transformed useful features from data and delivered and stored them in database using Cassandra and Zookeeper. After obtaining required features we applied machine learning and neural network algorithms in the data sets, to classify or mine potential knowledge. Finally we stored the results in MongoDB in which all staff from law enforce departments can have access to them through Web APP. We have applied several state-of-the-art data mining techniques and big data analytic tools that are specifically used for data processing and feature extraction. The experimental results show that our system is efficient in improving the filing rate, and also time-saving in processing large number of data. The promising outcomes will be beneficial for administrative enforcement and law enforcement to speed up the process of solving law cases and provide insights that enable them track case activities, predict the likelihood of warnings, effectively deploy resources and make faster decisions.