Formal Components of Narratives

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 701)

Abstract

One of the main problems of the current Digital Libraries (DLs) is the limitation of the informative services offered to the users, who express their queries in natural language. Indeed, DLs provide simple search functionalities that return a list of the information objects contained in them. No semantic relation among the returned objects is usually reported, which could help the user in obtaining a more complete knowledge on the subject of the search. The introduction of the Semantic Web, and in particular of the Linked Data, has the potential of improving the search functionalities of DLs. In this context, our final aim is to introduce the narrative as new first-class search functionality. As output of a query, the new search functionality does not only return a list of objects but it also presents a narrative, composed of events that are linked to the objects of the library and endowed with a set of semantic relations connecting these events into a meaningful semantic network. This paper presents a study of the Artificial Intelligence literature, especially of the Event Calculus theory, in order to identify the formal components of narratives. Furthermore, the mapping between these components and the standard ontology CIDOC CRM is presented, in order to evaluate if it could be taken as reference vocabulary to create an ontology for narratives. On the top of this ontology, we will develop the new search functionality for DLs.

Keywords

Digital libraries Formal components of narratives Narratives Ontologies Storytelling 

References

  1. 1.
    Agosti, M., Manfioletti, M., Orio, N., Ponchia, C.: Enhancing end user access to cultural heritage systems: tailored narratives and human-centered computing. In: Petrosino, A., Maddalena, L., Pala, P. (eds.) ICIAP 2013. LNCS, vol. 8158, pp. 278–287. Springer, Heidelberg (2013). doi:10.1007/978-3-642-41190-8_30 CrossRefGoogle Scholar
  2. 2.
    Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983)CrossRefMATHGoogle Scholar
  3. 3.
    Bringsjord, S., Ferrucci, D.: Artificial Intelligence and Literary Creativity: Inside the Mind of Brutus, a Storytelling Machine. Psychology Press, UK (1999)Google Scholar
  4. 4.
    Committee, P.E., et al.: Premis data dictionary for preservation metadata, version 2.0 (2008). Accessed 22 May 2010Google Scholar
  5. 5.
    Damiano, R., Lieto, A.: Ontological representations of narratives: a case study on stories and actions. In: OASIcs-OpenAccess Series in Informatics, vol. 32. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2013)Google Scholar
  6. 6.
    Davidson, D.: Essays on Actions and Events: Philosophical Essays, vol. 1. Oxford University Press, Oxford (2001)CrossRefGoogle Scholar
  7. 7.
    Doerr, M., Gradmann, S., Hennicke, S., Isaac, A., Meghini, C., van de Sompel, H.: The Europeana data model (EDM). In: World Library and Information Congress: 76th IFLA general conference and assembly, pp. 10–15 (2010)Google Scholar
  8. 8.
    Doerr, M., Ore, C.E., Stead, S.: The CIDOC conceptual reference model: a new standard for knowledge sharing. In: Tutorials, Posters, Panels and Industrial Contributions at the 26th International Conference on Conceptual Modeling, vol. 83, pp. 51–56. Australian Computer Society, Inc. (2007)Google Scholar
  9. 9.
    Fernie, K., Griffiths, J., Archer, P., Chandrinos, K., de Polo, A., Stevenson, M., Clough, P., Goodale, P., Hall, M., Agirre, E., et al.: Paths: personalising access to cultural heritage spaces. In: 2012 18th International Conference on Virtual Systems and Multimedia (VSMM), pp. 469–474. IEEE (2012)Google Scholar
  10. 10.
    Finlayson, M.A.: Inderjeet Mani. Computational Modeling of Narrative. Synthesis Lectures on Human Language Technologies, no. 18. Morgan & Claypool publishers, Seattle, WA (2013). ISBN 978-1-60845-981-0 (paperback: 40); ISBN 978-1-60845-982-7 (e-book: 30). xvii+ 124 p. (2014). doi:10.2200/s00459ed1v01y201212hlt018. Natural Language Engineering 20(02), 289–292Google Scholar
  11. 11.
    Gervás, P., Díaz-Agudo, B., Peinado, F., Hervás, R.: Story plot generation based on CBR. Knowl.-Based Syst. 18(4), 235–242 (2005)CrossRefGoogle Scholar
  12. 12.
    Harrell, D.A.: Theory and technology for computational narrative: an approach to generative and interactive narrative with bases in algebraic semiotics and cognitive linguistics (2007)Google Scholar
  13. 13.
    Hyvönen, E., Takala, J., Alm, O., Ruotsalo, T., Mäkelä, E.: Semantic kalevala-accessing cultural contents through semantically annotated stories. In: Proceedings of the Cultural Heritage on the Semantic Web Workshop at the 6th International SemanticWeb Conference (ISWC 2007), Busan, Korea. Citeseer (2007)Google Scholar
  14. 14.
    Kowalski, R., Sergot, M.: A logic-based calculus of events. In: Schmidt, J.W., Thanos, C. (eds.) Foundations of Knowledge Base Management, pp. 23–55. Springer, Heidelberg (1989)CrossRefGoogle Scholar
  15. 15.
    Lang, R.R.: A formal model for simple narratives (1997)Google Scholar
  16. 16.
    Lawrence, K.F., Jewell, M.O., Prugel-Bennett, A., et al.: Annotation of heterogeneous media using ontomedia (2006)Google Scholar
  17. 17.
    Lebowitz, M.: Story-telling as planning and learning. Poetics 14(6), 483–502 (1985)CrossRefGoogle Scholar
  18. 18.
    Liu, H., Singh, P.: Makebelieve: using commonsense knowledge to generate stories. In: AAAI/IAAI, pp. 957–958 (2002)Google Scholar
  19. 19.
    Lombardo, V., Damiano, R.: Semantic annotation of narrative media objects. Multimedia Tools Appl. 59(2), 407–439 (2012)CrossRefGoogle Scholar
  20. 20.
    McCarthy, J.: A basis for a mathematical theory of computation. Comput. Program. Formal Syst. 354, 225–238 (1963)Google Scholar
  21. 21.
    McCarthy, J., Hayes, P.J.: Some philosophical problems from the standpoint of artificial intelligence. Readings Artif. Intell., 431–450 (1969)Google Scholar
  22. 22.
    Meehan, J.R.: Tale-spin, an interactive program that writes stories. IJCAI 77, 91–98 (1977)Google Scholar
  23. 23.
    Meghini, C., Spyratos, N., Sugibuchi, T., Yang, J.: A model for digital libraries and its translation to RDF. J. Data Semant. 3(2), 107–139 (2014)CrossRefGoogle Scholar
  24. 24.
    Meister, J.C.: Computing Action: A Narratological Approach, vol. 2. Walter de Gruyter, New York (2003)Google Scholar
  25. 25.
    Miller, R., Shanahan, M.: Narratives in the situation calculus. J. Logic Comput. 4(5), 513–530 (1994)MathSciNetCrossRefMATHGoogle Scholar
  26. 26.
    Miller, R., Shanahan, M.: Some alternative formulations of the event calculus. In: Kakas, A.C., Sadri, F. (eds.) Computational Logic: Logic Programming and Beyond. LNCS (LNAI), vol. 2408, pp. 452–490. Springer, Heidelberg (2002). doi:10.1007/3-540-45632-5_17 CrossRefGoogle Scholar
  27. 27.
    Mueller, E.T.: Commonsense Reasoning: An Event Calculus Based Approach. Morgan Kaufmann, San Francisco (2014)Google Scholar
  28. 28.
    Mulholland, P., Collins, T.: Using digital narratives to support the collaborative learning and exploration of cultural heritage. In: Proceedings of 13th International Workshop on Database and Expert Systems Applications, pp. 527–531. IEEE (2002)Google Scholar
  29. 29.
    Pemberton, L.: A modular approach to story generation. In: Proceedings of the Fourth Conference on European Chapter of the Association for Computational Linguistics, pp. 217–224. Association for Computational Linguistics (1989)Google Scholar
  30. 30.
    PÉrez, R.P.Ý., Sharples, M.: Mexica: a computer model of a cognitive account of creative writing. J. Exp. Theor. Artif. Intell. 13(2), 119–139 (2001)Google Scholar
  31. 31.
    Propp, V.: Morphology of the Folktale, vol. 9. University of Texas Press, Austin (1973)Google Scholar
  32. 32.
    Raimond, Y., Abdallah, S.: The event ontology. Technical report (2007). http://motools.sourceforge.net/event
  33. 33.
    Riedl, M.O., Young, R.M.: Narrative planning: balancing plot and character. J. Artif. Intell. Res. 39(1), 217–268 (2010)MATHGoogle Scholar
  34. 34.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall, Egnlewood Cliffs, 25, 27 (1995)Google Scholar
  35. 35.
    Sandewall, E.: Filter preferential entailment for the logic of action in almost continuous worlds. Universitetet i Linköping/Tekniska Högskolan i Linköping, Institutionen för Datavetenskap (1989)Google Scholar
  36. 36.
    Scherp, A., Franz, T., Saathoff, C., Staab, S.: F-A model of events based on the foundational ontology dolce+DnS ultralight. In: Proceedings of the Fifth International Conference on Knowledge Capture, pp. 137–144. ACM (2009)Google Scholar
  37. 37.
    Shaw, R., Troncy, R., Hardman, L.: LODE: linking open descriptions of events. In: Gómez-Pérez, A., Yu, Y., Ding, Y. (eds.) ASWC 2009. LNCS, vol. 5926, pp. 153–167. Springer, Heidelberg (2009). doi:10.1007/978-3-642-10871-6_11 CrossRefGoogle Scholar
  38. 38.
    Shklovsky, V.: Art as technique Russian formalist criticism: four essays. In: Lemon, L.T., Reis, M.J. (eds.) University of Nebraska Press, Lincoln (1965)Google Scholar
  39. 39.
    Singh, P., et al.: The public acquisition of commonsense knowledge. In: Proceedings of AAAI Spring Symposium: Acquiring (and Using) Linguistic (and World) Knowledge for Information Access (2002)Google Scholar
  40. 40.
    Turner, S.R.: The Creative Process: A Computer Model of Storytelling and Creativity. Psychology Press, New York (1994)Google Scholar
  41. 41.
    Van Harmelen, F., Lifschitz, V., Porter, B.: Handbook of Knowledge Representation, vol. 1. Elsevier, Amsterdam (2008)MATHGoogle Scholar
  42. 42.
    Wolff, A., Mulholland, P., Collins, T.: Storyspace: a story-driven approach for creating museum narratives. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, pp. 89–98. ACM (2012)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Istituto di Scienza e Tecnologie dell’Informazione “Alessandro Faedo” – CNR PisaPisaItaly

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