Analyzing Chatbot Architectures Utilising Deep Neural Networks
This survey paper examines the advancements and challenges in chatbot technology, focusing on deep neural networks (DNNs) and their application in natural language processing (NLP). It discusses various chatbot models, including Elizabot, Alicebot, Mitsuku, and Cleverbot, highlighting their evolution from rule-based systems to sophisticated AI conversational agents. The study introduces a specialized chatbot for website integration, emphasizing the importance of swift, accurate, and personalized interactions to enhance customer engagement. Additionally, the paper explores the integration of Large Language Models (LLMs) such as Gemini, GPT and BERT, fine-tuning with deep learning techniques to improve chatbot performance, and their potential to revolutionize customer interactions and business growth.
Authors
- Rohit Patil (ORCID: https://orcid.org/0009-0005-8250-2382)
- Kshitij Kadam
- Anshul Thakur (ORCID: https://orcid.org/0000-0002-2859-0634)
- Kavita Patil
- Vedanti Koyande
Publication Details
- Published
- 2024-10-19
- DOI
- https://doi.org/10.1109/icccmla63077.2024.10871275
- Citations
- 3
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 1.04