Abstract
A topic ontology applies the usual ontological constructs to the task of annotating the topic of a document. The topic is the highly summarized essence of the document. The topics are usually chosen intuitively and rarely questioned. However, we have studied several ways of allocating frequently asked questions from a legal domain into a set of topical sub-domains. Our criteria were: 1) The sub-domains should not overlap. 2) The sub-domain should be objectively identifiable from the words of the text. 3) Which words and grammatical categories can serve as keywords? 4) Can the structure of sub-domains be induced semi-automatically from the text itself?
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Casellas, N., Jakulin, A., Vallbé, JJ., Casanovas, P. (2006). Acquiring an Ontology from the Text. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_107
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DOI: https://doi.org/10.1007/11779568_107
Publisher Name: Springer, Berlin, Heidelberg
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