International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Intelligent Chat Parser Based Smart Ordering System |
|---|---|
| ABSTRACT | Many ordering systems fail to handle natural, multilingual, and unstructured user inputs effectively, especially when users mix regional languages with English. To address this challenge, this project presents an Intelligent Chat Parser based Smart Ordering System that understands user messages and converts them into structured order data. The system uses a generative AI model integrated with a FastAPI backend to analyze user input, extract product names, quantities, and units, and return a valid JSON response. It supports multilingual and transliterated inputs, performs semantic validation on units, handles ambiguity through clarification prompts, and safely rejects restricted items. The parsed orders are stored for further processing, while users receive conversational replies in their original language. This approach improves order accuracy, user experience, and system reliability in chat-based ordering environments. |
| AUTHOR | DR. M. SENTHIL KUMAR, S. SATHISHKUMAR, MADHAN METHA S, KAVIN S, ARUN KUMAR B Professor, Department of Artificial Intelligence and Data Science, Kongunadu College of Engineering and Technology, Trichy, India Assistant Professor, Department of Artificial Intelligence and Data Science, Kongunadu College of Engineering and Technology, Trichy, India Department of Artificial Intelligence and Data Science, Kongunadu College of Engineering and Technology, Trichy, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1403013 |
| pdf/13_Intelligent Chat Parser Based Smart Ordering System.pdf | |
| KEYWORDS | |
| References | [1]. Brown, T., Mann, B., Ryder, N., et al., “Language Models are Few-Shot Learners”, Advances in Neural Information Processing Systems (NeurIPS), 2020. [2]. Chen, H., Liu, X., Yin, D., & Tang, J., “Dialogue Systems for Task-Oriented Applications”, ACM SIGKDD Explorations, 2017. [3]. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K., “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”, NAACL-HLT, 2019. [4]. Jurafsky, D., & Martin, J. H., Speech and Language Processing, 3rd Edition, Pearson Education, 2021. [5]. Kulkarni, S., Sadasivarao Korlakunta, M., Takawale, T. A., & Pandey, J. V., “Food Ordering Chatbot using Natural Language Processing”, International Journal of Science and Research Archive, 2025. [6]. Liu, X., Chen, H., Yin, D., & Tang, J., “Interactive Task-Oriented Dialogue Systems”, Proceedings of the AAAI Conference on Artificial Intelligence, 2018. [7]. Mesnil, G., Dauphin, Y., Yao, K., Bengio, Y., et al., “Intent Detection and Slot Filling for Spoken Language Understanding”, IEEE/ACM Transactions on Audio, Speech and Language Processing, 2015. [8]. OpenAI, “Prompt Engineering Techniques for Structured LLM Outputs”, Technical Report, 2023. [9]. Vaswani, A., Shazeer, N., Parmar, N., et al., “Attention Is All You Need”, Neural Information Processing Systems (NeurIPS), 2017. [10]. Zhao, T., & Eskenazi, M., “Towards End-to-End Learning for Dialog State Tracking”, SIGDIAL Conference, 2014. |
