Julian Seidenberg
ABSTRACT
Ontologies are at the heart of the semantic web. They define the concepts and relationships that make global interoperability possible. However, as these ontologies grow in size they become more and more difficult to create, use, understand, maintain, transform and classify. We present and evaluate several algorithms for extracting relevant segments out of large description logic ontologies for the purposes of increasing tractability for both humans and computers. The segments are not mere fragments, but stand alone as ontologies in their own right. This technique takes advantage of the detailed semantics captured within an OWL ontology to produce highly relevant segments. The research was evaluated using the GALEN ontology of medical terms and procedures.
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Index Terms
- Web ontology segmentation: analysis, classification and use
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Reviews
Klaus K. Obermeier
Research into the semantic Web has reached a breaking point. The ontologies or organized knowledge representation schemes have gotten so large that their usefulness for mundane everyday tasks is in jeopardy. What if we could design algorithms that would extract just the right amount of semantic information to solve domain-specific problems and challenges__?__ We could use subontologies fit for the task at hand, rather than entire ontologies. The authors propose such segmentation techniques and do so cogently in a very readable and commendable synopsis of the state of the art and the state of their research. They present various algorithms that allow the extraction of domain-specific knowledge representations from existing "mother lode" ontologies such as GALEN to increase tractability for specific needs or tasks to be accomplished. In their research, extraction by traversal creates an extract rather than a decomposition of ontologies as can be found in network partitioning or query-based methodologies. The authors test their hypothesis of extracting domain-specific ontologies from a larger all encompassing ontology such as GALEN (http://www.co-ode.org/galen) to arrive at "independently useful and usable ontologies" (page 21). They succeed in showing the importance of investigating algorithms to harness the power of existing ontologies. Investigating algorithms that extract from large ontologies makes evident the fact that it is not how knowledge is represented exhaustively, but how such knowledge is used judiciously. In brief, meaning is defined by its use, a statement that would make Wittgenstein proud. Online Computing Reviews Service
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