Researchers at Ain Shams University Have Published New Data on Human-Centric Int elligent Systems (Ontology-Based Enneagram Personality Prediction System)
Researchers at Ain Shams University Have Published New Data on Human-Centric Int elligent Systems (Ontology-Based Enneagram Personality Prediction System)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on human-centric int elligent systems have been published. According to news reporting originating fr om Ain Shams University by NewsRx correspondents, research stated, "Researchers are keen on finding out about people's emotions and interests. Personality predi ction helps in this issue." The news journalists obtained a quote from the research from Ain Shams Universit y: "Recognizing consumers' sentiments and desires assists in the development of better recommendation systems and dating applications. Previous personality pred iction systems studies had shown personality theories such as Big Five Traits, T hree Factor Model, etc. More informative personality model is required because i t offers a greater understanding. The target is enabling machines to understand the person more deeply than the previously used models. Enneagram is a distinct personality theory which demonstrates personalities' motivations, desires and fe ars. The questionnaire-based exam is the way to inform a person's Enneagram pers onality. People are not motivated to complete the exam because it takes time. En neagram personality prediction system is presented utilizing Enneagram personali ty model and Twitter text. This does not require any time or effort to predict t he personality of the Enneagram. Personality prediction of the Enneagram applies ontology, lexicon and a statistical method. The system's performance is evaluat ed using precision, recall, f1-score, and accuracy. The highest personality type recall output is the Enthusiast which is 95%."
Key words
Ain Shams University/Human-Centric Inte lligent Systems/Machine Learning
NETL
NSTL