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Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China
In this paper, we investigate an approach based on support vector machines (SVM) for analyzing and distinguishing plots of crime with computer, and propose a combination of database and learning scheme to improve the performance and efficiency. The support vector machine (SVM) is a machine-learning method which has been successfully applied to the forecasting area. To prove the feasibility of our assumption, we collect large amount of information concerning with laws、regulations、and judicial cases and take them as the training parameters of SVM to assist judge with crime. Due to the greatness of data, the processing speed is slow. We use data mining technology to search the best optimal data according to SVM algorithm. With the powerful learning and judging capacity of SVM, it can judge an approximate term of imprisonment to suspect which is a useful reference to judge. The ability of SVM to outperform several well-known methods developed for the intelligent search that SVM is a promising technique in the application of assisting judge to trial.