Tuning Schema Matching Systems using Parallel Genetic Algorithms on GPU

Tuning Schema Matching Software using Synthetic Scenarios

Most recent schema matching systems assemble multiple components, each employing a particular matching technique. The domain user must then tune the system: select the right component to be executed and correctly adjust their numerous “knobs” (e.g., thresholds, formula coefficients). Tuning is skilland time-intensive, but (as we show) without it the matching accuracy is significantly inferior. ...

MatchPlanner: A Self Tuning Tool for Planning Schema Matching Algorithms

To improve the matching accuracy, most of the schema matching tools aggregate the results obtained by several matching algorithms. The quality of matches depends on the adequacy and of the number of match algorithms used, and their combination and aggregation strategy. However, this aggregation entails several drawbacks on the performance, quality and tuning aspects. In this paper, we present a...

Planar character animation using genetic algorithms and GPU parallel computing

GPU-based Parallel Hybrid Genetic Algorithms

Over the last years, interest in hybrid metaheuristics has risen considerably in the field of optimization. Combinations of algorithms such as genetic algorithms (GAs) and local search (LS) methods have provided very powerful search algorithms. However, due to their complexity, the computational time of the solution search exploration remains exorbitant when large problem instances are to be so...

A Practical Schema Theorem for Genetic Algorithms Design and Tuning