Name
Title | ||
|---|---|---|
A Regression Dependent Iterative Algorithm for Optimizing Top-K Selection in Simulation Query Language |
Abstract | ||
|---|---|---|
In this paper the authors propose an extension of the algorithm General Optimal Regression Budget Allocation ScHeme GORBASH for iteratively optimizing simulation budget allocation while minimizing the total processing cost for top-k queries. They also implement this algorithm as part of SimQL: an extension of SQL that includes probability functions expressed through stochastic simulation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.4018/jdsst.2012070102 | IJDSST |
Keywords | Field | DocType |
optimizing top-k selection,top-k query,probability function,algorithm general optimal regression,regression dependent iterative algorithm,total processing cost,budget allocation scheme gorbash,stochastic simulation,simulation query language,iteratively optimizing simulation budget,database languages | Stochastic simulation,SQL,Data mining,Query language,Mathematical optimization,Regression,Iterative method,Computer science,Budget allocation,Uncertain data | Journal |
Volume | Issue | ISSN |
4 | 3 | 1941-6296 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Susan Farley | 1 | 6 | 2.16 |
| Alexander Brodsky | 2 | 510 | 92.99 |
| Chun-Hung Chen | 3 | 1095 | 117.31 |