MatchPlanner 
MatchPlanner uses a decision tree to combine the most appropriate similarity measures for a given domain. As a first consequence of using the decision tree for matching schemas, the time performance of the system is improved since the complexity is bounded by the height of the tree. The second advantage deals with the mappings quality. Indeed, for a given domain, only the most suitable similarity measures are used. Finally, MatchPlanner is also able to learn new decision trees, thus automatically tuning the system for providing optimal configuration for a given matching scenario.
Related publications
- A Flexible Approach for Planning Schema Matching Algorithms
OTM Conferences, CooPerative Information Systems (CooPIS), 2008
Fabien Duchateau and Zohra Bellahsene and Remi Coletta@inproceedings {coopis2008,
author = {Fabien Duchateau and Zohra Bellahsene and Remi Coletta},
title = {A Flexible Approach for Planning Schema Matching Algorithms},
booktitle = {OTM Conferences, CooPerative Information Systems (CooPIS)},
year = {2008},
pages = {249-264},
ee = {http://dx.doi.org/10.1007/978-3-540-88871-0_18},
url = {http://dx.doi.org/10.1007/978-3-540-88871-0_18},
bibsource = {DBLP, http://dblp.uni-trier.de},
}
Prototype
- Download the MatchPlanner tool (Unix version).
- Unzip the content of this archive. The subdirectory data contains scenarios, expert correspondences, etc.
- Run the script
run.shto launch MatchPlanner. - The GUI should let you use both the learner and the matcher.
Screenshots
