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@article{159244,
        author = {Prathamesh Jawale and Amit Narote and Frason Francis and Krishna More},
        title = {S3 DATA SUMMARIZATION AND VISUALIZATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {770-775},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159244},
        abstract = {Collecting and managing data has always been a difficulty, but with the arrival of AI and deep learning, the amount of data created has increased tremendously, resulting in Big Data. The sheer volume of unstructured data, which includes items like music, video, photos, and social network data, might make it challenging to exploit the information efficiently. The amount of text data available from various sources has increased dramatically. This amount of literature is an excellent source of information and expertise that must be adequately summarized to be useful. It becomes difficult for corporations to handle and process these papers promptly. To efficiently manage large amounts of text files, it is critical to evaluate and categorize the data. With this solution, we strive to create a platform that will provide quick and reliable summarization using various pre-trained natural language processing algorithms and visualization so that domain experts can get insights into the text data efficiently by fetching data from S3 buckets.},
        keywords = {S3 bucket, Cloud, Big Data, Natural Language, Transformer, Amazon Web Services.},
        month = {},
        }