Research On Assessment Methods Of The Judge Workload Base On Data Mining

With the development of the information technology in all walks of life,more and more data is accumulated.As a result of the demand of the times,data mining has attracted the attention of many departments,and it is a trend to use data mining technology to judge the workload of the judge.It is reasonable to assess the workload of judges,which is conducive to the correct allocation of the judges' posts and improve the quality of the trial.The workload of judges is an important factor in the judicial reform,If you can better assess the judge's workload,it will provide a lot of effective help to the judicial reform.At present,there are many courts in our country occur‘few judges deal with a lot of cases" and "many judges deal with few cases" situations,the reasonable allocation of judges is an urgent way to solve the problem,and the rational allocation of judges basically depends on the judge's workload.Judicial quality is the key target for judge work,also is to win the most basic requirements of judicial credibility.In ancient China has an idiom means "People credible,says it will do,a promise is a promise".The judge want to achieve fairness,justice and social credibility,the judge need speed time to understand the whole case and set up discussion groups to discuss the case and understand the scope of the legal application etc.Judicial efficiency is also a factor affecting the quality of the trial,the judge trial the case timely and efficient reflects the court's ability to solve problems.The above aspects fundamentally depends on the judge's workload,therefore,the judge workload has a significant influence on the trial quality.In ancient China there is a saying "Things of a kind come together,people of a kind fall into the same group",the thought of clustering has since ancient times.This paper uses two clustering algorithm to assess the workload of judges,one called improved K-means algorithm based on the attributes weighted,the second called the improved Chameleon algorithm.By analyzing the judge's job log,from several nodes which affect the workload of judge to analysis the workload of judge,using two improved algorithms to clustering the judge.According to the judges working time and the number of judges in each cluster we can judge the workload of the judge.In this paper,we discuss two improved clustering algorithms,we use a lot of other disciplines technology,which makes it more convincing in some aspects,and improve the accuracy of the algorithm.The judge can be engaged in many types of case trial,this paper mainly discusses the judges in the civil case,combined with the data which influenced the workload of the judge,using a variety of clustering algorithms analyze the workload of judges,so as to effectively evaluate judges workload.The purpose of data mining is mainly to obtain useful information,the users take advantage of these useful information to make decisions.Using data mining technology to solve problems in the current society,which has received the attention of many industry experts.According to different problems,data mining algorithm is also constantly improved.In this paper,the two kinds of clustering algorithm combined with the technology of different disciplines to analyze the judge's workload,which plays a certain role to reasonably assess the workload of judges.