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@article{172078,
        author = {Rakesh Kumar Giri},
        title = {KNOWLEDGE DISCOVERY AND DATA BASE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {3},
        number = {5},
        pages = {309-314},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172078},
        abstract = {KDD (Knowledge Discovery in Databases) is a technique for independently exploring and analyzing large datasets. Knowledge Discovery in Databases is a systematic procedure for identifying real, useful, innovative, and understandable patterns in large, complex data sets. The basis of this technology is data mining, which uses inference algorithms to examine data to create and discover previously unnoticed patterns. The application of theory to evidence makes it possible to analyze, predict, and understand events. Knowledge discovery and data mining are essential due to the accessibility and volume of data available today. Given the rapid growth of this field, it is not surprising that academics and practitioners have access to a variety of techniques. There is no method that always exceeds another. The data cover methodologies and methods for evaluating efficiency, demonstrate the use of various methods with examples of real applications and software tools, and seeks to assemble a complete catalog of all relevant methods developed in this area.},
        keywords = {KDD, Knowledge Discovery in Database, Data Mining, Data Repositories.},
        month = {January},
        }