Advertisement

Automatic Identification of Protagonist in Fairy Tales Using Verb

  • Hui-Ngo Goh
  • Lay-Ki Soon
  • Su-Cheng Haw
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7302)

Abstract

Named entity recognition (NER) has been a well-studied problem in the area of text mining for locating atomic element into predefined categories, where “name of people” is one of the most commonly studied categories. Numerous new NER techniques have been unfolded to accommodate the needs of the application developed. However, most research works carried out focused on non-fiction domain. Fiction domain exhibits complexity and uncertainty in locating protagonist as it represents name of person in a diverse spectrums, ranging from living things (animals, plants, person) to non-living things (vehicle, furniture). This paper proposes automated protagonist identification in fiction domain, particularly in fairy tales. Verb has been used as a determinant in substantiating the existence of protagonist with the assistance of WordNet. The experimental results show that it is viable to use verb in identifying named entity, particularly “people” category and it can be applied in a small text size environment.

Keywords

Named entity recognition characters fairy tales text mining 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chiticariu, L., Krishnamurthy, R., Li, Y.Y., Reiss, F., Vaithyanathan, S.: Domain Adaptation of Rule-Based Annotators for Named-Entity Recognition Tasks. In: Empirical Methods in Natural Language Processing, Massachusetts, pp. 1002 – 1012 (2010) Google Scholar
  2. 2.
    McCallum, A., Li, W.: Early Results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons. In: 7th Conference on Natural Language Learning, pp. 188–191 (2003) Google Scholar
  3. 3.
    Klein, D., Smarr, J., Nguyen, H., Manning, C.D.: Named Entity Recognition with Character-Level Models. In: 7th Conference on Natural Language Learning, pp. 180–183 (2003) Google Scholar
  4. 4.
    Irmak, U., Kraft, R.: A Scalable Machine-Learning Approach for Semi-Structured Named Entity Recognition. In: 19th International World Wide Web Conference, North Carolina, pp. 461–470 (2010) Google Scholar
  5. 5.
    Le, H.T., Nguyen, T.H.: Name Entity Recognition using Inductive Logic Programming. In: Symposium on Information and Communication Technology, Vietnam, pp. 71–77 (2010) Google Scholar
  6. 6.
    Minkov, E., Wang, R.C., Cohen, W.W.: Extracting Personal Names from Email: Applying Named Entity Recognition to Informal Text. In: Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Vancouver, pp. 443–450 (2005)Google Scholar
  7. 7.
    Sekine, S., Nobata, C.: Definition, Dictionaries and Tagger for Extended Named Entity Hierarchy. In: 4th International Conference on Language Resource and Evaluation (LREC), pp. 1977–1980 (2004) Google Scholar
  8. 8.
    Smarr, J., Manning, C.D.: Classifying Unknown Proper Noun Phrases without Context. Technical Report dbpubs/2002-46. Stanford University, Stanford, CA (2002) Google Scholar
  9. 9.
    Artiles, J., Amigo, E., Gonzalo, J.: The Role of Named Entities in Web People Search. In: Conference on Empirical Methods in Natural Language Processing, Singapore, pp. 534–542 (2009) Google Scholar
  10. 10.
    Fleischman, M., Hovy, E.: Fine Grained Classification of Named Entities. In: 19th International Conference on Computational Linguistics, pp. 1–7 (2002) Google Scholar
  11. 11.
    Elson, D.K., Dames, N., McKeown, K.R.: Extracting Social Networks from Literary Fiction. In: 48th Annual Meeting of the Association for Computational Linguistic, Uppsala, Sweden, pp. 138–147 (2010)Google Scholar
  12. 12.
    Goh, H.N., Kiu, C.C., Soon, L.K., Ranaivo, B.: Automatic Ontology Construction in Fiction-based Domain. International Journal of Software Engineering and Knowledge Engineering (2011) (in Press) Google Scholar
  13. 13.
    Klein, D., Manning, C.D.: Accurate Unlexicalized Parsing. In: 41st Meeting of the Association for Computational Lingusitic, pp. 423–430 (2003) Google Scholar
  14. 14.
    Stark, M.M., Riesenfeld, R.F.: WordNet: An Electronic Lexical Database. In: 11th Eurographics Workshop on Rendering (1998) Google Scholar
  15. 15.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hui-Ngo Goh
    • 1
  • Lay-Ki Soon
    • 1
  • Su-Cheng Haw
    • 1
  1. 1.Faculty of Computing and InformaticsMultimedia University, Jalan MultimediaCyberjayaMalaysia

Personalised recommendations