{"title":"LexrideLaw:一个基于争论的法律搜索引擎","authors":"Matthew Gifford","doi":"10.1145/3086512.3086548","DOIUrl":null,"url":null,"abstract":"Legal research search engines are overwhelmingly defined by adherence to the appellate case-law organizational model, whereby cases are discovered by relational keyword searches and case files are returned as results. We are proposing a new legal research search engine model where arguments are extracted from appellate cases and are accessible either through selecting nodes in a litigation issue ontology or through relational keyword searches.","PeriodicalId":425187,"journal":{"name":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"LexrideLaw: an argument based legal search engine\",\"authors\":\"Matthew Gifford\",\"doi\":\"10.1145/3086512.3086548\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Legal research search engines are overwhelmingly defined by adherence to the appellate case-law organizational model, whereby cases are discovered by relational keyword searches and case files are returned as results. We are proposing a new legal research search engine model where arguments are extracted from appellate cases and are accessible either through selecting nodes in a litigation issue ontology or through relational keyword searches.\",\"PeriodicalId\":425187,\"journal\":{\"name\":\"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3086512.3086548\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3086512.3086548","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Legal research search engines are overwhelmingly defined by adherence to the appellate case-law organizational model, whereby cases are discovered by relational keyword searches and case files are returned as results. We are proposing a new legal research search engine model where arguments are extracted from appellate cases and are accessible either through selecting nodes in a litigation issue ontology or through relational keyword searches.