Databases Reference
In-Depth Information
Chapter 10
Tuning for Schema Matching
Zohra Bellahsene and Fabien Duchateau
Abstract
Schema matching has long been heading towards complete automation.
However, the difficulty arising from heterogeneity in the data sources, domain speci-
ficity or structure complexity has led to a plethora of semi-automatic matching tools.
Besides, letting users the possibility to tune a tool also provides more flexibility,
for instance to increase the matching quality. In the recent years, much work has
been carried out to support users in the tuning process, specifically at higher levels.
Indeed, tuning occurs at every step of the matching process. At the lowest level,
similarity measures include internal parameters which directly impact computed
similarity values. Furthermore, a common filter to present mappings to users are
the thresholds applied to these values. At a mid-level, users can adopt one or more
strategies according to the matching tool that they use. These strategies aim at com-
bining similarity measures in an efficient way. Several tools support the users in
this task, mainly by providing state-of-the-art graphical user interfaces. Automat-
ically tuning a matching tool at this level is also possible, but this is limited to a
few matching tools. The highest level deals with the choice of the matching tool.
Due to the proliferation of these approaches, the first issue for the user is to find the
one which would best satisfies his/her criteria. Although benchmarking available
matching tools with datasets can be useful, we show that several approaches have
been recently designed to solve this problem.
B
Z. Bellahsene (
)
University of Montpellier II, 34000 Montpellier, France
e-mail:
bella@lirmm.fr
F. Duchateau
CWI, Amsterdam, The Netherlands
e-mail:
fabien@cwi.nl
