Schema Evolution publication categorizer

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 skill- and
time-intensive, but (as we show) without it the
matching accuracy is significantly inferior.
We describe eTuner, an approach to automatically tune schema matching systems. Given
a schema S, we match S against synthetic
schemas, for which the ground truth mapping

Semantic integration has been a long-standing challenge
for the database community. It has received
steady attention over the past two decades, and has
now become a prominent area of database research.
In this article, we first review database applications
that require semantic integration, and discuss the difficulties underlying the integration process. We then
describe recent progress and identify open research issues.
We will focus in particular on schema matching, a
topic that has received much attention in the database
community, but will also discuss data matching (e.g.,