Abstract:
Information integration with the aid of ontology can
roughly be divided into two levels: schema level and data
level. Most research has been focused on the schema level,
i.e., mapping/matching concepts and properties in different
ontologies with each other. However, the data level integration
is equally important, especially in the decentralized
Semantic Web environment. Noticing that ontology
data (in the form of instances of concepts) from different
sources often have different perspectives and may overlap
with each other, we develop a matching method that utilizes
the features of ontology and employs the machine learning
approach to integrate those instances. By exploring ontology
features, this method performs better than other general
methods, which is revealed in our experiments. Through
the process that implements the matching method, ontology
data can be integrated together to offer more sophisticated
services.
