Name
Abstract | ||
|---|---|---|
Queries posed to database systems often involve Universal Quantification. Such queries are typically expensive to evaluate. While they can be handled by basic access methods, for selection, grouping, etc., new access methods specifically tailored to evaluate universal quantification can greatly decrease the computational cost. In this paper, we study the efficient evaluation of universal quantification in an XML database. Specifically, we develop a small taxonomy of universal quantification types, and define a family of algorithms suitable for handling each. We experimentally demonstrate the performance benefits of the new family of algorithms. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TKDE.2007.190643 | IEEE Trans. Knowl. Data Eng. |
Keywords | Field | DocType |
performance benefit,new family,basic access method,database system,universal quantification type,universal quantification,computational cost,xml database,new access method,efficient evaluation,access method,database systems,algorithm design and analysis,xml,relational databases,indexes,access methods | Data mining,Algorithm design,Database query,XML,Access method,Relational database,Computer science,XML database,Artificial intelligence,Machine learning,Universal quantification | Journal |
Volume | Issue | ISSN |
19 | 11 | 1041-4347 |
Citations | PageRank | References |
2 | 0.40 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shurug Al-Khalifa | 1 | 402 | 21.76 |
| Bin Liu | 2 | 138 | 7.54 |
| H. V. Jagadish | 3 | 11141 | 2495.67 |