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解码职业成功:基于自适应神经模糊推理系统(ANFIS)建模的对数据科学专业人员的基于个性的分析。

Decoding career success: A personality-based analysis of data science Professional based on ANFIS modeling.

作者信息

Rezaiee Fard Ali, Amiri Babak

机构信息

School of Management, Economics and Progress Engineering, Iran University of Science and Technology, Iran.

School of Industrial Engineering, Iran University of Science and Technology, Iran.

出版信息

Heliyon. 2024 Jul 5;10(13):e34130. doi: 10.1016/j.heliyon.2024.e34130. eCollection 2024 Jul 15.

Abstract

Career selection is one of the most important decisions every person faces in their life. Finding the right career path can be a complicated task, particularly in choosing careers with similarly required proficiencies. One of the critical factors affecting a person's career success is their personality, and taking account of this factor is of paramount importance. This study uses the NEO-FFI questionnaire to find personality patterns of software engineering and data science experts based on the Big Five personality traits: Neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. Afterward, an ANFIS (Adaptive Network-Based Inference System) is conducted using the experts' personality data to match the participants of these fields with their corresponding choices. This study demonstrated that data scientists and software engineers score higher in conscientiousness and agreeableness, respectively. Also, data experts have higher scores in all traits overall. In the end, the ANFIS is tested with another similar dataset and the prediction accuracy of the model is measured.

摘要

职业选择是每个人一生中面临的最重要的决定之一。找到正确的职业道路可能是一项复杂的任务,尤其是在选择具有相似技能要求的职业时。影响一个人职业成功的关键因素之一是他们的个性,考虑这一因素至关重要。本研究使用NEO-FFI问卷,基于大五人格特质(神经质、外向性、经验开放性、宜人性和尽责性)来找出软件工程和数据科学专家的人格模式。之后,使用专家的人格数据进行自适应神经模糊推理系统(ANFIS)分析,以将这些领域的参与者与他们相应的选择相匹配。这项研究表明,数据科学家和软件工程师在尽责性和宜人性方面得分分别更高。此外,数据专家在所有特质上的总体得分更高。最后,使用另一个类似的数据集对ANFIS进行测试,并测量模型的预测准确性。

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