Mendeley
TY  _  JOUR
ID  -  A-10-2501-2
TI  -  An Intelligent Model for Multidimensional Personality Recognition of Users using Deep Learning Methods
JO  -  Journal of Information and Communication Technology
JA  -  ES
LA  -  fa
SN  -  2717-0411
AU  -  Sadr Hossein
AU  -   
AU  -   
AD  -  هیات علمی
AD  -  دانشجو
AD  -  استادیار
Y1  -  2021
PY  -  2021
VL  -  47
IS  -  
SP  -  72
EP  -  89
KW  -  Deep learning
KW  -   Convolutional neural network
KW  -   Adaboost combinational model
KW  -   Personality recognition
KW  -   Textual data
DO  -  
N2  -  Due to the significant growth of textual information and data generated by humans on social networks, there is a need for systems that can automatically analyze the data and extract valuable information from them. One of the most important textual data is people's opinions about a particular topic that are expressed in the form of text. Text published by users on social networks can represent their personality. Although machine learning based methods can be considered as a good choice for analyzing these data, there is also a remarkable need for deep learning based methods to overcome the complexity and dispersion of content and syntax of textual data during the training process. In this regard, the purpose of this paper is to employ deep learning based methods for personality recognition. Accordingly, the convolutional neural network is combined with the Adaboost algorithm to consider the possibility of using the contribution of various filter lengths and gasp their potential in the final classification via combining various classifiers with respective filter sizes using AdaBoost.  The proposed model was conducted on Essays and YouTube datasets. Based on the empirical results, the proposed model presented superior performance compared to other existing models on both datasets.
UR  - rimag.ir/en/Article/16362
L1  - rimag.ir/en/Article/Download/16362
ER  -  
