{"title":"概念近似方法的比较评价","authors":"J. Deogun, Liying Jiang","doi":"10.1109/ISDA.2005.35","DOIUrl":null,"url":null,"abstract":"Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Comparative evaluation on concept approximation approaches\",\"authors\":\"J. Deogun, Liying Jiang\",\"doi\":\"10.1109/ISDA.2005.35\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.\",\"PeriodicalId\":345842,\"journal\":{\"name\":\"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISDA.2005.35\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISDA.2005.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative evaluation on concept approximation approaches
Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.