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@article{193339,
        author = {Abhishek Yarraguddi and N. Siddartha Gowtham and M. Aaron Chris Lee and Dr. Ramesh Karnati},
        title = {Chatbot for Price Negotiation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {8302-8307},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193339},
        abstract = {The objective of the ”Chat-bot for Price Negotiation” convey is to develop an intelligent, artificial intelligence(AI)- driven chat bot which will drive pricing negotiations automatically and ease the process between buyers and sellers. The chat bot will apply machine learning(ML) and natural language processing (NLP) practice to assess user inputs, examine negotiation situations, and provide data-driven, real-time suggestions to optimize results for both parties. The system will be designed to handle a variety of negotiation situations, including business-to- business ( B2B ) transactions, service contracts, and online commence transactions. Sentiment analysis, dynamic pricing models, and personalized recommendations based on historical data and user behavior are some of the key characteristics. To ensure seamless user experiences, the chat bot will also engage with existing platforms. The goal of this project is to enhance efficiency, save time, and improve satisfaction in transactional interactions by automating negotiation tasks. The ultimate objective is to develop a user-friendly, scalable tool that enables user to reach equitable and mutually rewarding settlements with minimum effort.},
        keywords = {AI Chat bot , Price Negotiation ,Natural Language Processing (NLP), Dynamic Pricing.},
        month = {March},
        }