vaida-abstract
Abstract - lic thesis He Tan
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Aligning and Merging Biomedical Ontologies
Due to the explosion of the amount of biomedical data, knowledge and
tools that
are often publicly available over the Web, a number of difficulties are
experienced by biomedical researchers. For instance, it is difficult to
find,
retrieve and integrate information that is relevant to their research
tasks.
Ontologies and the vision of a Semantic Web for life sciences alleviate
these
difficulties.
In recent years many biomedical ontologies have been developed and many
of these
ontologies contain overlapping information. To be able to use
multiple
ontologies they have to be aligned or merged. A number of systems have
been
developed for aligning and merging ontologies and various alignment
strategies
are used in these systems. However, there are no general methods to
support
building such tools, and there exist very few evaluations of these
strategies.
In this thesis we give an overview of the existing systems. We propose
a general
framework for aligning and merging ontologies. Most existing systems
can be seen
as instantiations of this framework. Further, we develop SAMBO (System
for
Aligning and Merging Biomedical Ontologies) according to this
framework. We
implement different alignment strategies and their combinations, and
evaluate
them in terms of quality and processing time within SAMBO. We also
compare SAMBO
with two other systems. The work in this thesis is a first step towards
a
general framework that can be used for comparative evaluations of
alignment
strategies and their combinations.
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