• Speech Sciences
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• v.12 no.4
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• pp.129-139
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• 2005

This paper investigates any possible correlation between the information structure and the occurrence of clause internal pauses in the spontaneous discourse. One of the possible functions of pause is its capacity to signal the information structure of the discourse. However, this aspect was not much explored in Korean spontaneous speech. In the present study, information structure of spontaneous speech was defined for each word or word group on the basis of the information structure analysis model proposed by Van Donzel (1999) and Roulet (1991, 1997). Thus, at a local level (words or word groups) of discourse structure, a distinction was made between three types of information, new, given and inferable. The results showed that clause internal pauses tend to appear more frequently before new information than other types of information. However compared to the total number of words or word groups it was not noticed any specific ordering concerning different kind of information status and pausing. It was however found that clause internal pauses did not appear randomly. The majority of them occurred at the initial part of the clause or the sentence. This tendency was mostly related to the division of sentence (or clause) into topic and comment. Thus, the role of pauses as a marker of information structure seems to be less effective in spontaneous discourse.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.11-18
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• 2009

As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.