A database taxonomy based on data-driven knowledge modeling

被引:0
|
作者
Zellweger, P [1 ]
机构
[1] Arbor Way Labs, Cambridge, MA 02138 USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Taking a cue from data mining, the author employs a data model to capture data and its relationships in an RDBMS in order to create a database taxonomy. The combination of this data model and its mapping algorithms transform selected lists of data, or information, into an explicit knowledge representation. End-users view this taxonomy from a client interface that functions like database navigation structure. These advances redefine database access, as we know them, by enabling end-users to browse and explore database content. More importantly, this data-driven knowledge modeling capability lays the foundation for solving other, more challenging data access issues, namely machine-mediated access and database interoperability.
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收藏
页码:469 / 474
页数:6
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