• Karnam Akhil
• Dr.A. Brahmananda Reddy
• Abhinav Borad

In artificial intelligence (AI), knowledge mining employs modular services to learn from vast amounts of data quickly. Information can be understood and explored easier, hidden insights uncovered, and relationships and patterns found on a large scale. Artificial Intelligence (AI) has made it much easier to organize unstructured data and discover dark data. Knowledge mining can be automated by AI bots using advanced Machine Learning (ML) techniques. All your documents are crawled and understood, metadata is generated, and they are automatically classified and tagged. In addition to organizing your documents accurately, AI bots are more efficient and less expensive to run. Speed. Thus, enterprise search makes these documents easy to find. Knowledge mining is widely used in Deep-Learning, Machine- Learning, Artificial Intelligence, Data-Mining, Natural Language Processing, speech recognition, and many others. In this paper, different functionalities of knowledge mining are illustrated, and a framework is designed for the workflow of knowledge discovery in multi-disciplinary fields.

Knowledge Mining, Knowledge evaluation, Outlier analysis, Time-series analysis, Prediction

"A FRAMEWORK FOR KNOWLEDGE MINING IN MULTI-DISCIPLINARY FIELDS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.d496-d499, September-2022, Available :http://www.jetir.org/papers/JETIR2209359.pdf

"A FRAMEWORK FOR KNOWLEDGE MINING IN MULTI-DISCIPLINARY FIELDS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppd496-d499, September-2022, Available at : http://www.jetir.org/papers/JETIR2209359.pdf