Abstract
In this paper we present a novel method for ontology development that combines ontology learning and social-tagging process. The approach is based on the idea of using tagging process as a method for refinement (pruning) of the ontology that has been learned automatically from available knowledge sources. In the nutshell of the approach is a model for the conceptual tag refinement, which basically searches for terms that are conceptually related to the tags that are assigned to an information source. In that way the meaning of the tags can be disambiguated, which support better usage of the tagging process for the ontology pruning. We have developed a software tool, an annotation framework, which realizes this idea. We present results from the first evaluation studies regarding the application of this approach in the eGovernment domain.
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Stojanovic, L., Stojanovic, N., Ma, J. (2007). An Approach for Combining Ontology Learning and Semantic Tagging in the Ontology Development Process: eGovernment Use Case. In: Benatallah, B., Casati, F., Georgakopoulos, D., Bartolini, C., Sadiq, W., Godart, C. (eds) Web Information Systems Engineering – WISE 2007. WISE 2007. Lecture Notes in Computer Science, vol 4831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76993-4_21
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DOI: https://doi.org/10.1007/978-3-540-76993-4_21
Publisher Name: Springer, Berlin, Heidelberg
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