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Assessing American Presidential Candidates Using Principles of Ontological Engineering, Word Sense Disambiguation, and Data Envelope Analysis

Author

Listed:
  • James Rodger

    (IUP, United States)

  • Abdullah Murrar

    (IUP, United States)

  • Pankaj Chaudhary

    (IUP, United States)

  • Brandon Foley

    (IUP, United States)

  • Marouane Balmakhtar

    (IUP, United States)

  • Justin Piper

    (Penn State New Kensington, United States)

Abstract

Word Sense Disambiguation (WSD) is the process of automatically identifying which the appropriate meaning of a word given in its sentence. (WSD) is a promising research area in computational linguistics, especially in wide range of advanced applications, such as medical and social sciences. This research employs the concept (WSD) to determine the inherent meaning of voter intentions regarding possible political candidates. Where candidates can be examined and their true assets and competencies in three major areas of eligibility, education, and experience inputs can be deciphered. Data envelope analysis (DEA) is used to determine underlying word instances for elected and successful outputs. The results demonstrate the validity of using (DEA) as a tool for (WSD). The results also indicate that the survey administered by the website which is developed for the purpose of this research, and used in this study, is a promising tool for predicting successful presidential candidates.

Suggested Citation

  • James Rodger & Abdullah Murrar & Pankaj Chaudhary & Brandon Foley & Marouane Balmakhtar & Justin Piper, 2020. "Assessing American Presidential Candidates Using Principles of Ontological Engineering, Word Sense Disambiguation, and Data Envelope Analysis," Expanding Horizons: Business, Management and Technology for Better Society,, ToKnowPress.
    • Handle: RePEc:tkp:mklp20:81-108
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    References listed on IDEAS

    as
    1. Christian Zamo-Akono & Mondjeli M. Ndjokou & Simon Song-Ntamack, 2013. "Institutions and Hospital Efficiency in Cameroon: A Data Envelope Analysis," Journal of African Development, African Finance and Economic Association (AFEA), vol. 15(1), pages 45-71.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
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