Personality Detection Using Context Based Emotions in Cognitive Agents

IF 2 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI:10.32604/cmc.2022.021104

Nouh Sabri Elmitwally, Asma Kanwal, Sagheer Abbas, M. A. Khan, Muhammad Adnan Khan, Munir Ahmad, S. Alanazi

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引用次数: 4

Abstract

: Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper presents a conceptual personality model in cognitive agents that can determine personality and behavior based on some text input, using the context subjectivity of the given data and emotions obtained from a particular situation/context. The proposed work consists of Jumbo Chatbot, which can chat with humans. In this social interaction, the chatbot predicts human personality by understanding the emotions and context of interactive humans. Currently, the Jumbo chatbot is using the BFI technique to interact with a human. The accuracy of proposed work varies and improve through getting more experiences of interaction.

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基于情境情绪的认知代理人格检测

利用情感进行人格检测是人工智能的一个研究领域。目前，一些智能体可以保持人类的形象进行交互，并根据自己的喜好进行自我调整。然而，互动的有效方法是通过理解主体的情绪和背景来检测人的个性。在认知代理中添加个性背后的想法是试图在行为的基础上最大化适应性。在我们的日常生活中，人们通过分析音频或视觉输入的情感和互动背景来进行社交互动。本文提出了一种认知智能体的概念人格模型，该模型利用给定数据的语境主观性和从特定情境/语境中获得的情感，根据一些文本输入来确定人格和行为。提议的工作包括巨型聊天机器人，它可以与人类聊天。在这种社交互动中，聊天机器人通过理解互动人类的情绪和背景来预测人类的个性。目前，Jumbo聊天机器人正在使用BFI技术与人类互动。提出的工作的准确性是不同的，并通过获得更多的互动经验来提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cmc-computers Materials & Continua 工程技术-材料科学：综合

CiteScore

5.30

自引率

19.40%

发文量

345

审稿时长

1 months

期刊介绍： This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.