Tensor Flow-Based Automatic Personality Recognition

TensorFlow Based Automatic personality prediction is the process of using artificial intelligence (AI) and machine learning algorithms to predict a person’s personality. It attempts to identify the traits, attitudes, and behaviors of a person by analyzing their data, such as their speech, text, or other activities.

This system uses the big five personality traits, namely, Openness, Agreeableness, Neuroticism, Extraversion and Conscientiousness for prediction of personality of a person. These traits are the best accepted and most commonly used model of personality in academic psychology. The test consists of 20 questions that the user must rate on how true they are about them on a 3-point scale where Agree, Neural and Disagree values 0, 1, and 2 accordingly. According to the obtained marks of the user the personality is predicted. For the prediction purpose, a training dataset including marks and an adjective for a personality is fed to the model for training. Here, we use KNN and Logistic Regression classifiers.

This system also includes TF algorithm which calculates the term frequency in a document or a file. Here, we extract the table of contents from a document file uploaded by the user, and then calculate the term frequency of each word in the document using TF algorithm. The aim of this algorithm in this project is to check the word frequency in the user’s technical skills and work history and hence decide on what is he good at.

Application :

• This type of prediction has been used in a variety of applications such as
• Job recruiting
• Social media analysis
• Customer service.