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An ontology-based approach for resolving semantic schema conflicts in the extraction and integration of query-based information from heterogeneous web data sources
Hajmoosaei, A. and Abdul Kareem, S.
There are many external resources and heterogeneous
data on the internet that an organization or user may need
to improve the decision making process. It is therefore,
very important and critical that this information are
complete, precise and can be acquired on time. Most web
sources provide data in semi-structured form on the
internet. The combination of semi-structured data from
different sources on the internet often fails because of
syntactic and semantic differences. The access, retrieval
and utilization of information from the different web data
sources impose a need for the data to be integrated.
Integration of web data is a complex process because of
the heterogeneity nature of web data and thus needs some
kind of a web data integration system. There are many
types of heterogeneity and differences among web
sources that makes data integration a difficult process
(e.g., different data model, different syntax and semantics
in schema and data instance level among web sources).
Semantic schema heterogeneity, which refers to the
misinterpretation of data at the schema level, is one major
obstacle that needs to be overcome in web data
integration process. Semantic schema heterogeneity has
been identified as one of the most important problems
when dealing with interoperability and cooperation
among multiple data sources on the internet. In this paper,
we recommend a system architecture for web data
integration focusing on resolving the problems of
semantic schema heterogeneity between web data
sources. We propose an ontology-based approach as a
solution for the reconciliation of semantic conflicts
between web data at the schema level.
Cite as: Hajmoosaei, A. and Abdul Kareem, S. (2007). An ontology-based approach for resolving semantic schema conflicts in the extraction and integration of query-based information from heterogeneous web data sources. In Proc. Third Australasian Ontology Workshop (AOW 2007), Gold Coast, Australia. CRPIT, 85. Meyer, T. and Nayak, A. C., Eds. ACS. 35-43.
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