{"title":"从关系数据库中提取符号对象","authors":"Véronique Stéphan","doi":"10.1109/DEXA.1996.558606","DOIUrl":null,"url":null,"abstract":"Our aim is to define operators to retrieve groups of individuals from a relational database. The way we describe these groups makes it possible to analyse them by symbolic data analysis methods which extend classical ones to more complex data. In so far as the input consists of groups of data extensionally defined in the database, our problem is to find the best description representing each group in the formalism (called symbolic object) of symbolic data analysis. In our process, we take into account data from tables together with additional knowledge such as taxonomies. To describe each group, we perform a generalization step and a specialization one. Final descriptions are based on the notion of homogeneity within a group and they minimize a volume criterion.","PeriodicalId":438695,"journal":{"name":"Proceedings of 7th International Conference and Workshop on Database and Expert Systems Applications: DEXA 96","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Extracting symbolic objects from relational databases\",\"authors\":\"Véronique Stéphan\",\"doi\":\"10.1109/DEXA.1996.558606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our aim is to define operators to retrieve groups of individuals from a relational database. The way we describe these groups makes it possible to analyse them by symbolic data analysis methods which extend classical ones to more complex data. In so far as the input consists of groups of data extensionally defined in the database, our problem is to find the best description representing each group in the formalism (called symbolic object) of symbolic data analysis. In our process, we take into account data from tables together with additional knowledge such as taxonomies. To describe each group, we perform a generalization step and a specialization one. Final descriptions are based on the notion of homogeneity within a group and they minimize a volume criterion.\",\"PeriodicalId\":438695,\"journal\":{\"name\":\"Proceedings of 7th International Conference and Workshop on Database and Expert Systems Applications: DEXA 96\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 7th International Conference and Workshop on Database and Expert Systems Applications: DEXA 96\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEXA.1996.558606\",\"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 7th International Conference and Workshop on Database and Expert Systems Applications: DEXA 96","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.1996.558606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting symbolic objects from relational databases
Our aim is to define operators to retrieve groups of individuals from a relational database. The way we describe these groups makes it possible to analyse them by symbolic data analysis methods which extend classical ones to more complex data. In so far as the input consists of groups of data extensionally defined in the database, our problem is to find the best description representing each group in the formalism (called symbolic object) of symbolic data analysis. In our process, we take into account data from tables together with additional knowledge such as taxonomies. To describe each group, we perform a generalization step and a specialization one. Final descriptions are based on the notion of homogeneity within a group and they minimize a volume criterion.