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https://hdl.handle.net/10356/155153
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mehta, Yash | en_US |
dc.contributor.author | Majumder, Navonil | en_US |
dc.contributor.author | Gelbukh, Alexander | en_US |
dc.contributor.author | Cambria, Erik | en_US |
dc.date.accessioned | 2022-02-14T08:01:45Z | - |
dc.date.available | 2022-02-14T08:01:45Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Mehta, Y., Majumder, N., Gelbukh, A. & Cambria, E. (2020). Recent trends in deep learning based personality detection. Artificial Intelligence Review, 53(4), 2313-2339. https://dx.doi.org/10.1007/s10462-019-09770-z | en_US |
dc.identifier.issn | 0269-2821 | en_US |
dc.identifier.uri | https://hdl.handle.net/10356/155153 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Artificial Intelligence Review | en_US |
dc.rights | © 2019 Springer Nature B.V. All rights reserved. | en_US |
dc.subject | Engineering::Computer science and engineering | en_US |
dc.title | Recent trends in deep learning based personality detection | en_US |
dc.type | Journal Article | en |
dc.contributor.school | School of Computer Science and Engineering | en_US |
dc.identifier.doi | 10.1007/s10462-019-09770-z | - |
dc.identifier.scopus | 2-s2.0-85074520909 | - |
dc.identifier.issue | 4 | en_US |
dc.identifier.volume | 53 | en_US |
dc.identifier.spage | 2313 | en_US |
dc.identifier.epage | 2339 | en_US |
dc.subject.keywords | Personality Detection | en_US |
dc.subject.keywords | Multimodal Interaction | en_US |
dc.description.acknowledgement | A. Gelbukh recognizes the support of the Instituto Politecnico Nacional via the Secretaria de Investigacion y Posgrado projects SIP 20196437 and SIP 20196021. | en_US |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | SCSE Journal Articles |
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