{"title":"关于矛盾论点的稳定法律知识","authors":"Shingo Hagiwara, S. Tojo","doi":"10.5555/1166890.1166945","DOIUrl":null,"url":null,"abstract":"A large size of legal knowledge base which consists of entangled inference rules, facts, and arbitrary interpretations may latently include inconsistency within them. In this paper, we propose a method to find the source of such inconsistency by supplying hypothesized facts into a set of rules. With this, we put those rules in the order of reliability and show a stable part of the legal knowledge. First, we define an argument as a chaining of rules to support a certain proposition. Thereafter, we compose a minimal inconsistency set (MIS) combining two disagreeing arguments. Among such a MIS, we can distinguish stable rules that is indifferent to the source of inconsistent from unstable rules, which can be candidates of future amendment. A knowledge-base which consists of stable rules can be also distinguished from that which may contain unstable rules.","PeriodicalId":91205,"journal":{"name":"Artificial intelligence and applications (Commerce, Calif.)","volume":"265 1","pages":"323-328"},"PeriodicalIF":0.0000,"publicationDate":"2006-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Stable Legal Knowledge with Regard to Contradictory Arguments\",\"authors\":\"Shingo Hagiwara, S. Tojo\",\"doi\":\"10.5555/1166890.1166945\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A large size of legal knowledge base which consists of entangled inference rules, facts, and arbitrary interpretations may latently include inconsistency within them. In this paper, we propose a method to find the source of such inconsistency by supplying hypothesized facts into a set of rules. With this, we put those rules in the order of reliability and show a stable part of the legal knowledge. First, we define an argument as a chaining of rules to support a certain proposition. Thereafter, we compose a minimal inconsistency set (MIS) combining two disagreeing arguments. Among such a MIS, we can distinguish stable rules that is indifferent to the source of inconsistent from unstable rules, which can be candidates of future amendment. A knowledge-base which consists of stable rules can be also distinguished from that which may contain unstable rules.\",\"PeriodicalId\":91205,\"journal\":{\"name\":\"Artificial intelligence and applications (Commerce, Calif.)\",\"volume\":\"265 1\",\"pages\":\"323-328\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial intelligence and applications (Commerce, Calif.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5555/1166890.1166945\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial intelligence and applications (Commerce, Calif.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5555/1166890.1166945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stable Legal Knowledge with Regard to Contradictory Arguments
A large size of legal knowledge base which consists of entangled inference rules, facts, and arbitrary interpretations may latently include inconsistency within them. In this paper, we propose a method to find the source of such inconsistency by supplying hypothesized facts into a set of rules. With this, we put those rules in the order of reliability and show a stable part of the legal knowledge. First, we define an argument as a chaining of rules to support a certain proposition. Thereafter, we compose a minimal inconsistency set (MIS) combining two disagreeing arguments. Among such a MIS, we can distinguish stable rules that is indifferent to the source of inconsistent from unstable rules, which can be candidates of future amendment. A knowledge-base which consists of stable rules can be also distinguished from that which may contain unstable rules.