{"title":"FURY:基于编辑距离的模糊统一和分辨率","authors":"D. Gilbert, M. Schroeder","doi":"10.1109/BIBE.2000.889625","DOIUrl":null,"url":null,"abstract":"The authors present a theoretically founded framework for fuzzy unification and resolution based on edit distance over trees. Their framework extends classical unification and resolution conservatively. They prove important properties of the framework and develop the FURY system, which implements the framework efficiently using dynamic programming. The authors evaluate the framework and system on a large problem in the bioinformatics domain, that of detecting typographical errors in an enzyme name database.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"FURY: fuzzy unification and resolution based on edit distance\",\"authors\":\"D. Gilbert, M. Schroeder\",\"doi\":\"10.1109/BIBE.2000.889625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors present a theoretically founded framework for fuzzy unification and resolution based on edit distance over trees. Their framework extends classical unification and resolution conservatively. They prove important properties of the framework and develop the FURY system, which implements the framework efficiently using dynamic programming. The authors evaluate the framework and system on a large problem in the bioinformatics domain, that of detecting typographical errors in an enzyme name database.\",\"PeriodicalId\":196846,\"journal\":{\"name\":\"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBE.2000.889625\",\"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 IEEE International Symposium on Bio-Informatics and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBE.2000.889625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FURY: fuzzy unification and resolution based on edit distance
The authors present a theoretically founded framework for fuzzy unification and resolution based on edit distance over trees. Their framework extends classical unification and resolution conservatively. They prove important properties of the framework and develop the FURY system, which implements the framework efficiently using dynamic programming. The authors evaluate the framework and system on a large problem in the bioinformatics domain, that of detecting typographical errors in an enzyme name database.