DocumentCode
2404143
Title
Extensible and similarity-based grouping for data integration
Author
Schallehn, Eike ; Sattler, Kai-Uwe ; Saake, Gunter
Author_Institution
Dept. of Comput. Sci., Univ. of Magdeburg, Germany
fYear
2002
fDate
2002
Firstpage
277
Abstract
The general concept of grouping and aggregation appears to be a fitting paradigm for various issues in data integration, but in its common form of equality-based grouping, a number of problems remain unsolved. We propose a generic approach to user-defined grouping as part of a SQL extension, allowing for more complex functions, for instance integration of data mining algorithms. Furthermore, we discuss high-level language primitives for common applications
Keywords
SQL; data mining; high level languages; merging; SQL extension; common applications; data integration; data mining algorithms; equality-based grouping; extensible similarity-based grouping; high-level language primitives; user-defined grouping; Computer science; Conferences; Data mining; Engines; Fitting; High level languages; Information systems; Packaging; Systems engineering and theory; Warehousing;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2002. Proceedings. 18th International Conference on
Conference_Location
San Jose, CA
ISSN
1063-6382
Print_ISBN
0-7695-1531-2
Type
conf
DOI
10.1109/ICDE.2002.994731
Filename
994731
Link To Document