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@article{196834,
        author = {uday shankar simhadri},
        title = {Float Chat: A Conversational AI Framework for Interactive Exploration for ARGO Oceanographic Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {5058-5070},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196834},
        abstract = {The increasing availability of oceanographic data, driven by global observation initiatives such as the ARGO float network, has created new opportunities for marine research and environmental monitoring. However, extracting meaningful insights from these large-scale datasets remains challenging for users without specialized technical expertise. This paper presents Float Chat, an intelligent conversational framework designed to simplify the exploration and analysis of ARGO ocean data. The proposed system integrates natural language processing, structured data retrieval, analytical processing, and visualization techniques to enable users to interact with oceanographic datasets through intuitive textual queries. By translating user input into executable data operations, the system retrieves relevant measurements and generates interpretable outputs in both textual and graphical formats. Experimental evaluation demonstrates that the platform effectively reduces the complexity of ocean data analysis while improving accessibility for non-expert users. The proposed approach contributes to the advancement of environmental data analytics by enabling interactive, user-centric access to marine information and supporting applications in climate research, ocean monitoring, and education.},
        keywords = {Conversational AI, ARGO Oceanographic Data, Natural Language Processing, Ocean Data Visualization, Environmental Data Analytics, Marine Data Exploration, Intelligent Data Systems},
        month = {April},
        }