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Linguistic Description of the Evolution of Stress Level Using Fuzzy Deformable Prototypes

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 853))

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Abstract

The purpose of this paper is to show that it is possible to describe stress levels through a complete time-log analysis. For this purpose it has been developed a fuzzy deformable prototypes based model that uses a fuzzy representation of the prototypical situations. The proposed model has been applied to a database composed of time logs from students with and without stress. Preliminary results from the proposed model application have been validated by experts. Moreover, the model has been applied as a classifier obtaining good results for both sensitivity and specificity. Finally, the proposal has been validated and should be considered useful for the expert systems design to support the stress level description.

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References

  1. Kumar, G., Jerbi, H., Gurrin, C., O’Mahony, M.P.: Towards activity recommendation from lifelogs. In: Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services, pp. 87–96. ACM (2014). https://doi.org/10.1145/2684200.2684298

  2. Wang, P., Smeaton, A.F.: Using visual lifelogs to automatically characterize everyday activities. Inf. Sci. 230, 147–161 (2013). https://doi.org/10.1016/j.ins.2012.12.028

    Article  Google Scholar 

  3. Dobbins, C., Rawassizadeh, R., Momeni, E.: Detecting physical activity within lifelogs towards preventing obesity and aiding ambient assisted living. Neurocomputing 230, 110–132 (2017). https://doi.org/10.1016/j.neucom.2016.02.088

    Article  Google Scholar 

  4. Kim, H.H., Lee, S.Y., Baik, S.Y., Kim, J.H.: MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices. Int. J. Med. Inf. 84(12), 1099–1110 (2015). https://doi.org/10.1016/j.ijmedinf.2015.08.005

    Article  Google Scholar 

  5. Pavlidis, T.: Structural Pattern Recognition. Springer, Heidelberg (1977). https://doi.org/10.1007/978-3-642-88304-0

    Book  MATH  Google Scholar 

  6. Grundy, E.: Extraction and Classification of Features in Accelerometry Data Doctoral dissertation, Swansea University (2008)

    Google Scholar 

  7. Zadeh, L.A.: A note on prototype theory and fuzzy sets. In: Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems, pp. 587–593 (1996). https://doi.org/10.1142/9789814261302-0027. Selected Papers by Lotfi A Zadeh

    Google Scholar 

  8. Olivas, J.A., Sobrino, A.: An application of Zadeh’s prototype theory to the prediction of forest fire in a knowledge-based system. In: Proceedings of the 5th International IPMU, vol. 2, pp. 747–752 (1994)

    Google Scholar 

  9. Bremermann, H.: Pattern recognition by deformable prototypes. In: Hilton, P. (ed.) Structural Stability, the Theory of Catastrophes, and Applications in the Sciences. LNM, vol. 525, pp. 15–57. Springer, Heidelberg (1976). https://doi.org/10.1007/BFb0077842

    Chapter  Google Scholar 

  10. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Mag. 17(3), 37 (1996)

    Google Scholar 

  11. Vazquez, M.R., Romero, F.P., Olivas, J.A., Orbe, E., Serrano-Guerrero, J.: An approach to academic performance prediction in tutoring systems based on fuzzy deformable prototypes. Prog. Artif. Intell. 5(1), 55–64 (2016). https://doi.org/10.1007/s13748-015-0074-9

    Article  Google Scholar 

  12. Trivino, G., Sugeno, M.: Towards linguistic descriptions of phenomena. Int. J. Approx. Reason. 54(1), 22–34 (2013). https://doi.org/10.1016/j.ijar.2012.07.004

    Article  Google Scholar 

  13. Yager, R.R.: Fuzzy summaries in database mining. In: Proceedings of the 11th Conference on Artificial Intelligence for Applications, CAIA 1995, p. 265 (1995). https://doi.org/10.1109/CAIA.1995.378813

  14. Zadeh, L.A.: A computational approach to fuzzy quantifiers in natural languages. Comput. Math. Appl. 9(1), 149–184 (1983). https://doi.org/10.1016/0898-1221(83)90013-5

    Article  MathSciNet  MATH  Google Scholar 

  15. Teigen, K.H.: Yerkes-Dodson: A law for all seasons. Theory Psychol. 4(4), 525–547 (1994). https://doi.org/10.1177/0959354394044004

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Information Technologies and Systems, University of Castilla La Mancha, Ciudad Real, Spain

    Francisco P. Romero, José A. Olivas & Jesus Serrano-Guerrero

Authors
  1. Francisco P. Romero
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  2. José A. Olivas
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  3. Jesus Serrano-Guerrero
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Corresponding author

Correspondence to Francisco P. Romero .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Universidad de Granada, Granada, Spain

    David A. Pelta

  5. Universidad de Málaga, Málaga, Málaga, Spain

    Inma P. Cabrera

  6. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Romero, F.P., Olivas, J.A., Serrano-Guerrero, J. (2018). Linguistic Description of the Evolution of Stress Level Using Fuzzy Deformable Prototypes. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-91473-2_38

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  • DOI: https://doi.org/10.1007/978-3-319-91473-2_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91472-5

  • Online ISBN: 978-3-319-91473-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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