The Design And Implementation Of Legal Service System Based On Natural Language Processing

With the steady progress of the construction of national legalization,the system of judicial publicity has been gradually formed.Referee documents,as the carrier of judicial proceedings,have been publicized according to law in the Internet.At the same time,with the development of Natural Language Processing technology,its integration with big data is becoming more and more popular.It is the starting point of this article to deal with the big data of referee documents and excavate potential values through Natural Language Processing technology.When the user has a lawsuit demand,it will help the user understand the scope of the responsibility of the case to a great extent if it can retrieve the referee documents of the case by entering the information of the case.This semantic similarity is applied to case documents retrieval.It is of certain significance to promote the construction of the country's legal system.On the basis of the research of big data referee documents and Natural Language Processing technology,the thesis designs the keyword extraction algorithm and the similarity calculation algorithm of the referee's documents first.The two algorithms is designed to extract keyword information of the referee documents and calculate the similarity of the referee documents.Based on two algorithms,a forensic service system is designed and implemented.The system takes data from the data acquisition layer as the data background.System information extraction layer and storage layer are responsible for the extraction and storage of key documents of referee.The system service layer will give full play to the advantages of Natural Language Processing technology and big data integration,it provide semantic search of similar case for users.The system is coordinated at all levels,and the whole design process is clear.The system passed the functional test and performance test smoothly,and it achieved the initial design goal.