AI-Based Chatbot Systems: Architectures, Applications, and Future Trends

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@article{1711981,
      author = {Shweta Tarade, Tanvi Mokashie, Pranjali Yadav, Shreya Nikam, Prof. Prajwal pawar},
      title = {AI-Based Chatbot Systems: Architectures, Applications, and Future Trends},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {785-797},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1711981.pdf},
      abstract = {Artificial Intelligence (AI) has enabled the creation of intelligent systems capable of understanding and interacting with humans naturally. Among its many applications, the AI-based chatbot stands out as one of the most widely used and influential innovations. A chatbot is a conversational agent that uses Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL) to engage in human-like communication through text or speech. It can analyze queries, understand intent, and generate meaningful responses in real-time. This review paper provides a detailed study of AI chatbot development, architectures, methodologies, and use cases across domains such as education, healthcare, customer service, and e-commerce. It reviews more than 25 recent research papers (2020?2025) and integrates case studies of real-world systems like ChatGPT, IBM Watson, Google Bard, and Replika. The paper discusses the evolution of chatbots from early rule-based systems to transformer-based models, identifies current challenges such as context management, ethics, and scalability, and explores future trends in multimodal chatbots, emotion detection, and explainable AI.},
      keywords = {Artificial Intelligence (AI), Chatbots, Natural Language Processing (NLP), Machine Learning (ML), Deep Learning, Conversational AI, Transformer Models, Generative AI.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1711981}
  }