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Recent trends in deep learning based personality detection

Mehta, Yash ; Majumder, Navonil ; Gelbukh, Alexander ; Cambria, Erik

The Artificial intelligence review, 2020-04, Vol.53 (4), p.2313-2339 [Periódico revisado por pares]

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Título:
Recent trends in deep learning based personality detection
Autor: Mehta, Yash ; Majumder, Navonil ; Gelbukh, Alexander ; Cambria, Erik
Assuntos: Affective computing ; Artificial Intelligence ; Computer Science ; Deep learning ; Forecasts and trends ; Industrial applications ; Machine learning ; Personality ; Personality traits
É parte de: The Artificial intelligence review, 2020-04, Vol.53 (4), p.2313-2339
Descrição: Recently, the automatic prediction of personality traits has received a lot of attention. Specifically, personality trait prediction from multimodal data has emerged as a hot topic within the field of affective computing. In this paper, we review significant machine learning models which have been employed for personality detection, with an emphasis on deep learning-based methods. This review paper provides an overview of the most popular approaches to automated personality detection, various computational datasets, its industrial applications, and state-of-the-art machine learning models for personality detection with specific focus on multimodal approaches. Personality detection is a very broad and diverse topic: this survey only focuses on computational approaches and leaves out psychological studies on personality detection.
Editor: Dordrecht: Springer Netherlands
Idioma: Inglês

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