Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

An Ontology-Based Approach to Metaphor Cognitive Computation

  • Published:
Minds and Machines Aims and scope Submit manuscript

Abstract

Language understanding is one of the most important characteristics for human beings. As a pervasive phenomenon in natural language, metaphor is not only an essential thinking approach, but also an ingredient in human conceptual system. Many of our ways of thinking and experiences are virtually represented metaphorically. With the development of the cognitive research on metaphor, it is urgent to formulate a computational model for metaphor understanding based on the cognitive mechanism, especially with the view to promoting natural language understanding. Many works have been done in pragmatics and cognitive linguistics, especially the discussions on metaphor understanding process in pragmatics and metaphor mapping representation in cognitive linguistics. In this paper, a theoretical framework for metaphor understanding based on the embodied mechanism of concept inquiry is proposed. Based on this framework, ontology is introduced as the knowledge representation method in metaphor understanding, and metaphor mapping is formulated as ontology mapping. In line with the conceptual blending theory, a revised conceptual blending framework is presented by adding a lexical ontology and context as the fifth mental space, and a metaphor mapping algorithm is proposed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. http://www.keenage.com.

  2. http://ckip.iis.sinica.edu.tw/taxonomy/taxonomy-doc.htm.

  3. http://ccl.pku.eu.cn/ccl_sem_dict/.

References

  • Anderson, M. L. (2003). Embodied cognition: A field guide. Artificial Intelligence, 149(1), 91–130.

    Article  Google Scholar 

  • Baader, F., Calvanese, D., McGuinness, D., Nardi, D., & Patel-Schneider, P. (2003). The description logic handbook. Cambridge: Cambridge University Press.

    MATH  Google Scholar 

  • Boden, M. A. (2003). The creative mind: Myths and mechanisms. London: Routledge.

    Google Scholar 

  • Chen, K. J., Shu-Ling, H., Yueh-Yin, S., & Yi-Jun, C. (2005). Extended-hownet: A representational framework for concepts. In OntoLex 2005—ontologies and lexical resources IJCNLP-05 workshop, Jeju Island, South Korea.

  • Dong, Z. D., & Dong, Q. (2006). Hownet and the computation of meaning. Singapore: World Scientific Publishing Company.

    Book  Google Scholar 

  • Fauconnier, G., & Turner, M. (1998). Conceptual integration networks. Cognitive Science, 22(2), 133–187.

    Article  Google Scholar 

  • Fauconnier, G., & Turner, M. (2002). The way we think: Conceptual blending and the mind’s hidden complexities. London: Basic Books.

    Google Scholar 

  • Fellbaum, C. (1998). WordNet: An electronic lexical database. Cambridge: MIT Press.

    MATH  Google Scholar 

  • Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7, 155–170.

    Article  Google Scholar 

  • Gomez-Perez, A., & Corcho, O. (2002). Ontology languages for the semantic web. IEEE Intelligent Systems, 17(4), 54–60.

    Article  Google Scholar 

  • Grady, J., Oakley, T., & Coulson, S. (1997). Blending and metaphor. In W. G. Raymond, & J. S. Gerard (Eds.), Metaphor in cognitive linguistics (pp. 101–124). Amsterdam: John Benjamins Publishing Company.

    Google Scholar 

  • Gruber, T. (1993). A translation approach to portable ontology specification. Knowledge Acquisition, 5, 199–220.

    Article  Google Scholar 

  • Guarino, N. (1998). Formal ontology and information systems. In Proceedings of 1st International conference on formal ontology in information systems (FOIS’98) (pp. 3–5). Trento, Italy: The IOS Press.

  • Huang, X. X. (2009). Research on some key issues of metaphor computation. PhD thesis, Zhejiang University, Hangzhou, China (in Chinese).

  • Huang, X. X., & Zhou, C. L. (2005). A logical approach for metaphor understanding. In Proceedings of 2005 IEEE International conference on natural language processing and knowledge engineering (pp. 268–271). Wuhan, China: IEEE Computer Society.

  • Huang, X. X., & Zhou C. L. (2007). An owl-based wordnet lexical ontology. Journal of Zhejiang University (Science A), 8(6), 864–870.

    Article  MathSciNet  MATH  Google Scholar 

  • Huang, X. X., Huang, H. X., Xu, C. H., Chen, W., & Wang, R. B. (2011). A novel a novel pattern matching method for chinese metaphor identification and classification. In Proceedings of the 2011 International conference on artificial intelligence and computational intelligence (AICI’11) (pp. 104–114). Taiyuan, China: Springer.

  • Johnson, M. (1989). The body in the mind: The bodily basis of meaning, imagination, and reason. Chicago: The University of Chicago Press.

    Google Scholar 

  • Kittay, E. F. (1987). Metaphor, its cognitive force and linguistic structure. Oxford, USA: Oxford University Press.

    Google Scholar 

  • Kovecses, Z. (2010). Metaphor: A practical introduction, 2nd ed. Oxford: Oxford University Press.

    Google Scholar 

  • Lakoff, G. (1987). Women, fire, and dangerous things. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: The University of Chicago Press.

    Google Scholar 

  • Lakoff, G., & Johnson, M. (1999). Philosophy in the flesh: The embodied mind and its challenge to western thought. New York: Basic books.

    Google Scholar 

  • Lakoff, G., & Turner, M. (1989). More than cool reason: A field guide to poetic metaphor. Chicago: Chicago University Press.

    Book  Google Scholar 

  • Maedche, A., & Volz, R. (2001). The ontology extraction and maintenance framework text-to-onto. In Proceedings of the ICDM’ 01 workshop on integrating data mining and knowledge management, California, USA (pp. 1–12).

  • Mason, Z. J. (2004). Cormet: A computational, corpus-based conventional metaphor extraction system. Computational Linguistics, 30(1), 23–44.

    Article  Google Scholar 

  • Miller, G. A. (1993). Images and models, similes and metaphors. In A. Ortony (Ed.), Metaphor and thought, metaphor and thought (pp. 357–400). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Ogden, C. K., & Richards, I. A. (1989). The meaning of meaning. New York: Mariner Books.

    Google Scholar 

  • Pereira, F. C. (2007). Creativity and artificial intelligence: A conceptual blending approach. Berlin: Mouton de Gruyter.

    Google Scholar 

  • Shutova, E. (2010). Models of metaphor in nlp. In Proceedings of the 48th annual meeting of the association for computational linguistics, Uppsala, Sweden (pp. 688–697).

  • Sowa, J. F. (2000). Knowledge representation: Logical, philosophical, and computational foundations. Pacific Grove, CA: Brooks Cole Publishing Co.

    Google Scholar 

  • Steinhart, E. C. (2001). The logic of metaphor: Analogous parts of possible worlds. Dordrecht: Kluwer.

    Google Scholar 

  • Veale, T. (1995). Metaphor, memory and meaning: Symbolic and connectionist issues in metaphor interpretation. PhD thesis, Trinity College, Dublin.

  • Yang, Y., Zhou, C. L., Ding, X. J., Chen, J. W., & Shi, X. D. (2009). Metaphor recognition: Chmeta, a pattern-based system. Computational Intelligence, 25(4), 265–301. doi:10.1111/j.1467-8640.2009.00349.x.

    Article  MathSciNet  Google Scholar 

  • Zhou, C. L. (2003). Introduction to mind computation. Beijing: Tsinghua University Press.

    Google Scholar 

  • Zhou, C. L., Yang, Y., & Huang, X. X. (2007). Computational mechanisms for metaphor in languages: A survey. Journal Computer Science and Technology, 22(2), 308–319.

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This research is supported in part by research grants from the National Natural Science Foundation of China for Young Scientists(No.61103101), the Major Program of National Social Science Foundation of China(No.11&ZD088), the Humanity and Social Sciences Foundation for Young Scholars of China’s Ministry of Education (No.10YJCZH052), the Zhejiang Provincial Natural Science Foundation of China (No.Y1080606), the China Postdoctoral Science Foundation(No.20100481443 and No.201104743).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaoxi Huang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Huang, X., Huang, H., Liao, B. et al. An Ontology-Based Approach to Metaphor Cognitive Computation. Minds & Machines 23, 105–121 (2013). https://doi.org/10.1007/s11023-012-9269-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11023-012-9269-z

Keywords

Navigation