{"title":"基于多元学习方法的刑事定罪分类","authors":"Xi Yang, Xudong Luo, Ying Liu","doi":"10.1109/ISKE47853.2019.9170293","DOIUrl":null,"url":null,"abstract":"The application of artificial intelligence in the legal field can save a lot of the time for legal professionals. In particular, in this paper we propose a method for predicting what kind of conviction a suspect has according to the facts of the crime of the suspect. Specifically, we first pre-process the data and then use multiple classification methods to classify the crime facts, and finally combine the results of each model to gain a more accurate of conviction classification.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Criminal Conviction Classification Based on Multiple Learning Methods\",\"authors\":\"Xi Yang, Xudong Luo, Ying Liu\",\"doi\":\"10.1109/ISKE47853.2019.9170293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of artificial intelligence in the legal field can save a lot of the time for legal professionals. In particular, in this paper we propose a method for predicting what kind of conviction a suspect has according to the facts of the crime of the suspect. Specifically, we first pre-process the data and then use multiple classification methods to classify the crime facts, and finally combine the results of each model to gain a more accurate of conviction classification.\",\"PeriodicalId\":399084,\"journal\":{\"name\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"117 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISKE47853.2019.9170293\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE47853.2019.9170293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Criminal Conviction Classification Based on Multiple Learning Methods
The application of artificial intelligence in the legal field can save a lot of the time for legal professionals. In particular, in this paper we propose a method for predicting what kind of conviction a suspect has according to the facts of the crime of the suspect. Specifically, we first pre-process the data and then use multiple classification methods to classify the crime facts, and finally combine the results of each model to gain a more accurate of conviction classification.
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