A Study of Retrieval Model Providing Relevant Sentences in Storytelling on Semantic Web

이태영

doi:10.3743/KOSIM.2009.26.4.007

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Vol.26 No.4

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A Study of Retrieval Model Providing Relevant Sentences in Storytelling on Semantic Web

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073

2009, v.26 no.4, pp.7-34

https://doi.org/10.3743/KOSIM.2009.26.4.007

(2009). A Study of Retrieval Model Providing Relevant Sentences in Storytelling on Semantic Web. Journal of the Korean Society for Information Management, 26(4), 7-34, https://doi.org/10.3743/KOSIM.2009.26.4.007

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Abstract

Structures of stories, paragraphs, and sentences and inferences applied to indexing and searching were studied to construct the full-text and sentence retrieval system for storytelling. The system designed the database of stories, paragraphs, and sentences and the knowledge-base of inference rules to aid to write the story. The Knowledge-base comprised the files of story frames, paragraph scripts, and sentence logics made by mark-up languages like SWRL etc. able to operate in semantic web. It is necessary to establish more precise indexing language represented the sentences and to create a mark-up languages able to construct more accurate inference rules.

keywords: storytelling, semantic web, fact retrieval, knowledge-base, sentence retieval, paragraph retrieval, inference rule, storytelling, semantic web, fact retrieval, knowledge-base, sentence retieval, paragraph retrieval, inference rule, 이야기 쓰기, 시맨틱, 웹, 사항검색, 지식베이스, 문장검색, 단락검색, 추론규칙

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