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@article{175401,
        author = {Soham Ingale and Aryan Vartak and Aditya Kallurkar and Suhas Waghmare},
        title = {Transformative Text Analysis and Processing Using NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2740-2745},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175401},
        abstract = {In the digital era, the demand for efficient text- processing tools has surged due to the exponential increase in textual data. Existing Natural Language Processing (NLP) applications provide solutions for specific tasks such as grammar correction, lemmatization, stemming, part-of-speech (POS) tagging, and sentiment analysis. However, users often need to navigate multiple platforms to perform these tasks, leading to inefficiencies. This paper proposes a unified NLP platform that integrates multiple text-processing functionalities, enabling users to perform comprehensive text analysis in a single interface. The proposed system is developed using Python and Django and leverages advanced NLP techniques to provide accurate and real- time text analysis. The study highlights the architecture, implementation, and performance evaluation of the system. Experimental results demonstrate the efficiency of the platform in enhancing text-processing tasks.},
        keywords = {Natural Language Processing (NLP), Text Analysis, Grammar Correction, Lemmatization, Stemming, POS Tagging, Sentiment Analysis.},
        month = {April},
        }