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

James Rodger, Abdullah Murrar, Pankaj Chaudhary, Brandon Foley, Marouane Balmakhtar and Justin Piper
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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

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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.

Keywords: Artificial Intelligence; Data Envelope Analysis; Ontological Engineering; Word- Sense Disambiguation (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:tkp:mklp20:81-108

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