Mapping complex metadata structures is crucial in a number of domains such as
data integration, ontology alignment or model management. To speed up that
process automatic matching systems were developed to compute mapping
suggestions that can be corrected by a user. However, constructing and tuning
match strategies still requires a high manual effort by matching experts as
well as correct mappings to evaluate generated mappings. We therefore propose a
self-configuring schema matching system that is able to automatically adapt to
the given mapping problem at hand. Our approach is based on analyzing the input
schemas as well as intermediate matching results. A variety of matching rules
use the analysis results to automatically construct and adapt an underlying
matching process for a given match task. We comprehensively evaluate our
approach on different mapping problems from the schema, ontology and model
management domains. The evaluation shows that our system is able to robustly
return good quality mappings across different mapping problems and domains.
%0 Generic
%1 Peukert2011
%A Peukert, Eric
%A Eberius, Julian
%A Rahm, Erhard
%D 2011
%K mapping match_merge matching metadata
%T Rule-based Construction of Matching Processes
%U http://arxiv.org/ftp/arxiv/papers/1108/1108.1925.pdf
%X Mapping complex metadata structures is crucial in a number of domains such as
data integration, ontology alignment or model management. To speed up that
process automatic matching systems were developed to compute mapping
suggestions that can be corrected by a user. However, constructing and tuning
match strategies still requires a high manual effort by matching experts as
well as correct mappings to evaluate generated mappings. We therefore propose a
self-configuring schema matching system that is able to automatically adapt to
the given mapping problem at hand. Our approach is based on analyzing the input
schemas as well as intermediate matching results. A variety of matching rules
use the analysis results to automatically construct and adapt an underlying
matching process for a given match task. We comprehensively evaluate our
approach on different mapping problems from the schema, ontology and model
management domains. The evaluation shows that our system is able to robustly
return good quality mappings across different mapping problems and domains.
@misc{Peukert2011,
abstract = { Mapping complex metadata structures is crucial in a number of domains such as
data integration, ontology alignment or model management. To speed up that
process automatic matching systems were developed to compute mapping
suggestions that can be corrected by a user. However, constructing and tuning
match strategies still requires a high manual effort by matching experts as
well as correct mappings to evaluate generated mappings. We therefore propose a
self-configuring schema matching system that is able to automatically adapt to
the given mapping problem at hand. Our approach is based on analyzing the input
schemas as well as intermediate matching results. A variety of matching rules
use the analysis results to automatically construct and adapt an underlying
matching process for a given match task. We comprehensively evaluate our
approach on different mapping problems from the schema, ontology and model
management domains. The evaluation shows that our system is able to robustly
return good quality mappings across different mapping problems and domains.
},
added-at = {2011-08-11T10:04:44.000+0200},
author = {Peukert, Eric and Eberius, Julian and Rahm, Erhard},
biburl = {https://www.bibsonomy.org/bibtex/2d6d472aa84183a844987bb1c98add8a6/maxirichter},
description = {Rule-based Construction of Matching Processes},
interhash = {8190b86ddc16b3bfd6322eea5b46967b},
intrahash = {d6d472aa84183a844987bb1c98add8a6},
keywords = {mapping match_merge matching metadata},
note = {cite arxiv:1108.1925 Comment: 10 Pages},
timestamp = {2012-01-16T12:42:14.000+0100},
title = {Rule-based Construction of Matching Processes},
url = {http://arxiv.org/ftp/arxiv/papers/1108/1108.1925.pdf},
year = 2011
}