Abstract
Data believability estimation is a crucial issue in many application domains. This is particularly true when handling uncertain input data given by Alzheimer’s disease patients. In this paper, we propose an approach, called DBE_ALZ, to estimate quantitatively the believability of uncertain input data in the context of applications for Alzheimer’s disease patients. In this context, data may be given by Alzheimer’s disease patients or their caregivers. The believability of an input data is estimated based on its reasonableness compared to common-sense standard and personalized rules and the reliability of its authors. This estimation is based on Bayesian networks and Mamdani fuzzy inference systems. We illustrate the usefulness of our approach in the context of the Captain Memo memory prosthesis. Finally, we discuss the encouraging results de-rived from the evaluation of our approach.
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References
Métais, E., et al.: Memory prosthesis. In: Non-Pharmacological Therapies in Dementia (2015)
Herradi, N., Hamdi, F., Métais, E., Ghorbel, F., Soukane, A.: PersonLink: an ontology representing family relationships for the CAPTAIN MEMO memory prosthesis. In: Jeusfeld, Manfred A., Karlapalem, K. (eds.) ER 2015. LNCS, vol. 9382, pp. 3–13. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25747-1_1
Wang, R., Strong, D.: Beyond accuracy: what data quality means to data consumers. J. Manag. Inf. Syst. 12(4), 5–33 (1996)
Pipino, L., Lee, Y., Wang, R.: Data quality assessment. Commun. ACM 45, 211–218 (2002)
Hong, T.: Contributing factors to the use of health-related websites. J. Health Commun. 11(2), 149–165 (2006)
Lee, Y.W., Pipino, L.L., Fund, J.F., Wang, R.Y.: Journey to Data Quality. The MIT Press, Cambridge (2006)
Prat, N., Madnick, S.: Measuring data believability: a provenance approach. In: Hawaii International Conference on System Sciences, p. 393, Los Alamitos, CA, USA (2008)
Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning. Int. J. Inf. Sci. 9(1), 301–357 (1975)
Folstein, M.F., Folstein, S.E., McHugh, P.R.: Mini mental state: a practical method for grading the cognitive state of patients for clinician. J. Psychiatry Res. 12, 189–198 (1975)
Ghorbel, F., Ellouze, N., Métais, E., Hamdi, F., Gargouri, F.: MEMO_Calendring: a smart reminder for Alzheimer’s disease patients. In: International Conference on Smart, Monitored and Controlled Cities, p. 6, Sfax, Tunisie (2017)
Cingolani, P., Alcala-Fdez, J.: jFuzzyLogic: a robust and flexible fuzzy-logic inference system language implementation. In: International Conference on Fuzzy Systems, pp. 1–8 (2012)
Cozman, F.: The JavaBayes system. ISBA Bull. 7(4), 16–21 (2001)
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Ghorbel, F., Hamdi, F., Métais, E. (2019). Estimating the Believability of Uncertain Data Inputs in Applications for Alzheimer’s Disease Patients. In: Métais, E., Meziane, F., Vadera, S., Sugumaran, V., Saraee, M. (eds) Natural Language Processing and Information Systems. NLDB 2019. Lecture Notes in Computer Science(), vol 11608. Springer, Cham. https://doi.org/10.1007/978-3-030-23281-8_17
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DOI: https://doi.org/10.1007/978-3-030-23281-8_17
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