个性和职业兴趣识别数据集的创建

Abel Robles Montoya, M. L. B. Estrada, Ramón Zatarain Cabada, Héctor Manuel Cárdenas López, Arcelia Judith Bustillos Martínez
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引用次数: 0

摘要

本文介绍了收集个性和职业兴趣数据的方法和工具;测量人格和兴趣的模型分别为HEXACO和RIASEC。创建该数据集的目的是在训练阶段将其用于预测模型。用这个数据集训练的模型被用在一个系统中,该系统包括从一个短视频中预测一个人的职业兴趣。结果是包含127个完整测试记录和98个视频的最终数据集。由于这些数据的局限性,这些数据以一种人格价值和兴趣范围不完整的方式分布,导致识别器的显着不平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creation of a Dataset for personality and professional interest recognition
This paper presents the methodology and tools developed for the collection of data on personality and vocational interests; the models selected to measure personality and interests are HEXACO and RIASEC respectively. The objective of creating this dataset is use it in prediction models during the training phase. The models trained with this dataset are used in a system which includes all to predict a person's vocational interests from a short video. The results were a final dataset with 127 completed test records and 98 videos. As limitations these data are distributed in a way that the range of values of personality and interests are not complete, causing a significant imbalance for the recognizers.
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