An interaction framework of service-oriented ontology learning

ABSTRACT

Ontology plays a very important role in supporting knowledge-based applications. In cloud computing, ontology learning technology is facing new challenges in dealing with heterogeneous data sources from different domains and researchers, which may contain various particular concepts and relations. Traditional ontology learning frameworks usually focus only on the extraction of concepts and taxonomic relations from the multi-structured corpus. However, former researches rarely studied the interactions during ontology learning process among different researchers. Lack of interactions among people who build ontology in different domains may cause inconsistent ontology. Besides, lack of incentive during the ontology building process will also result in low efficiency. To address these challenges, this paper specifies a novel solution to perform ontology learning. The solution includes a service-oriented ontology interaction framework, a service-oriented ontology learning strategy. It shows that it advances ontology learning to a higher level of performance and portability with a number of experiments in demo system.

References

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Index Terms

• Computing methodologies

  • Machine learning

    • Learning settings