{"title":"基于已有规则构建本体的新算法:一个案例研究","authors":"Faten F. Kharbat, Haya Ghalayini","doi":"10.1109/ICIME.2009.16","DOIUrl":null,"url":null,"abstract":"From the fact that ontologies can help in making sense of huge amount of content, this paper proposes a case study for building ontology via set of rules generated by rule-based learning system. The proposed algorithm utilises the extracted and representative rules generated from the original dataset in developing ontology elements. The proposed algorithm is applied to a well known dataset in the breast cancer domain. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for ontology development.","PeriodicalId":445284,"journal":{"name":"2009 International Conference on Information Management and Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"New Algorithm for Building Ontology from Existing Rules: A Case Study\",\"authors\":\"Faten F. Kharbat, Haya Ghalayini\",\"doi\":\"10.1109/ICIME.2009.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"From the fact that ontologies can help in making sense of huge amount of content, this paper proposes a case study for building ontology via set of rules generated by rule-based learning system. The proposed algorithm utilises the extracted and representative rules generated from the original dataset in developing ontology elements. The proposed algorithm is applied to a well known dataset in the breast cancer domain. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for ontology development.\",\"PeriodicalId\":445284,\"journal\":{\"name\":\"2009 International Conference on Information Management and Engineering\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Information Management and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIME.2009.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Information Management and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIME.2009.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New Algorithm for Building Ontology from Existing Rules: A Case Study
From the fact that ontologies can help in making sense of huge amount of content, this paper proposes a case study for building ontology via set of rules generated by rule-based learning system. The proposed algorithm utilises the extracted and representative rules generated from the original dataset in developing ontology elements. The proposed algorithm is applied to a well known dataset in the breast cancer domain. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for ontology development.