ISRST

An interest based storytelling model using rhetorical relations

Arturo Nakasone, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Most storytelling model approaches consider stories formed by sequences of a particular type of event. These sequences are mostly constructed using the inherent temporal characteristic of each linked event and this limitation makes it difficult to adapt the models to other kinds of events. In order to develop a more generic model to create storytelling applications, we need to organize events using not only temporal relations, but also relations determined by the rhetorical context of those events. In this paper, we present ISRST, our proposal for a generic storytelling ontology model based on the organization of events using a subset of relations proposed by the Rhetorical Structure Theory and how narrative principles and user interest are applied to these relations to generate coherent stories.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages324-335
Number of pages12
Volume4469 LNCS
Publication statusPublished - 2007
Externally publishedYes
Event2nd International Conference on Edutainment, Edutainment 2007 - Hong Kong
Duration: 2007 Jun 112007 Jun 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4469 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Conference on Edutainment, Edutainment 2007
CityHong Kong
Period07/6/1107/6/13

Fingerprint

Storytelling
Model
Ontology
Model-based
Subset
Narrative

Keywords

  • Interactive storytelling
  • Ontology model
  • Rhetorical relations
  • RST
  • User interest

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Nakasone, A., & Ishizuka, M. (2007). ISRST: An interest based storytelling model using rhetorical relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4469 LNCS, pp. 324-335). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4469 LNCS).

ISRST : An interest based storytelling model using rhetorical relations. / Nakasone, Arturo; Ishizuka, Mitsuru.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4469 LNCS 2007. p. 324-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4469 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nakasone, A & Ishizuka, M 2007, ISRST: An interest based storytelling model using rhetorical relations. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4469 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4469 LNCS, pp. 324-335, 2nd International Conference on Edutainment, Edutainment 2007, Hong Kong, 07/6/11.
Nakasone A, Ishizuka M. ISRST: An interest based storytelling model using rhetorical relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4469 LNCS. 2007. p. 324-335. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Nakasone, Arturo ; Ishizuka, Mitsuru. / ISRST : An interest based storytelling model using rhetorical relations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4469 LNCS 2007. pp. 324-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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