TY - GEN
T1 - A Cognitive Intelligent Personalized Virtual Assistant Chatbot for Improved User Interactivity
AU - Mishra, Mandakani
AU - Mishra, Sushruta
AU - Yang, Tiansheng
AU - Wang, Lu
AU - Rathore, Bharati
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2026/1/2
Y1 - 2026/1/2
N2 - Realistic virtual assistants and conversational chatbots are transforming human–computer interaction through great personalization, context awareness, and conversation. This paper comes out with recent advancements in AI and NLP that have improved the realism of these digital agents. Yet, even though this is great progress, there are areas of challenge still cut across accurately understanding user intent, maintenance of context over extended conversations, and ethical issues such as privacy and bias. This paper synthesizes recent literature to outline the trends, persistent challenges, and emerging solutions facing chatbots toward developing more realistic models. In essence, this paper presents a new model that combines advanced AI techniques to improve the quality of user interaction. The results from our analysis are that a stride has been made toward the capabilities of virtual assistants in machine learning, particularly deep learning, with the understanding that more research remains to be done to solve some of these outstanding issues that still affect the quality of such experiences for users.
AB - Realistic virtual assistants and conversational chatbots are transforming human–computer interaction through great personalization, context awareness, and conversation. This paper comes out with recent advancements in AI and NLP that have improved the realism of these digital agents. Yet, even though this is great progress, there are areas of challenge still cut across accurately understanding user intent, maintenance of context over extended conversations, and ethical issues such as privacy and bias. This paper synthesizes recent literature to outline the trends, persistent challenges, and emerging solutions facing chatbots toward developing more realistic models. In essence, this paper presents a new model that combines advanced AI techniques to improve the quality of user interaction. The results from our analysis are that a stride has been made toward the capabilities of virtual assistants in machine learning, particularly deep learning, with the understanding that more research remains to be done to solve some of these outstanding issues that still affect the quality of such experiences for users.
KW - Chatbots
KW - Conversational AI
KW - Deep learning
KW - Natural language processing (NLP)
KW - Reinforcement learning
KW - Virtual assistants
U2 - 10.1007/978-981-96-8343-7_3
DO - 10.1007/978-981-96-8343-7_3
M3 - Conference contribution
AN - SCOPUS:105028299873
SN - 9789819683420
T3 - Lecture Notes in Networks and Systems
SP - 23
EP - 34
BT - Proceedings of International Conference on Computing Systems and Intelligent Applications - ComSIA 2025
A2 - Jaiswal, Ajay
A2 - Anand, Sameer
A2 - Hassanien, Aboul Ella
A2 - Azar, Ahmad Taher
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Computing Systems and Intelligent Applications, ComSIA 2025
Y2 - 28 March 2025 through 29 March 2025
ER -