{"title":"A data model and access method for summary data management","authors":"Meng Chang Chen, L. McNamee","doi":"10.1109/ICDE.1989.47220","DOIUrl":null,"url":null,"abstract":"A data model and an access method for summary data management are proposed. Summary data, represented as a trinary tuple , consist of metaknowledge summarized by a statistical function of a category of individual information typically stored in a conventional database. The concept of category (type or class) and the additivity property of statistical functions form a basis for the model that allows for the derivation of summary data. The complexity of deriving summary data has been found computationally intractable in general, and the proposed summary data model, with disjointness constraint, solves the problem without the loss of information. The proposed access method, called the summary data tree, or SD-tree, which handles an orthogonal category as a hyperrectangle, realizes the proposed summary data model. The structure of the SD-tree provides for efficient operations including summary data search, derivation, and insertion on the stored summary data.<<ETX>>","PeriodicalId":329505,"journal":{"name":"[1989] Proceedings. Fifth International Conference on Data Engineering","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. Fifth International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1989.47220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
Abstract
A data model and an access method for summary data management are proposed. Summary data, represented as a trinary tuple , consist of metaknowledge summarized by a statistical function of a category of individual information typically stored in a conventional database. The concept of category (type or class) and the additivity property of statistical functions form a basis for the model that allows for the derivation of summary data. The complexity of deriving summary data has been found computationally intractable in general, and the proposed summary data model, with disjointness constraint, solves the problem without the loss of information. The proposed access method, called the summary data tree, or SD-tree, which handles an orthogonal category as a hyperrectangle, realizes the proposed summary data model. The structure of the SD-tree provides for efficient operations including summary data search, derivation, and insertion on the stored summary data.<>