Machine Learning Techniques for Advanced Knowledge Management

Mark Sanderson

Machine Learning Techniques for Advanced Knowledge Management

Author(s)	Mark Sanderson
Country	Australia
Abstract	The rapid expansion of digital information has transformed knowledge management into a critical component of modern organizational and research environments. Organizations increasingly generate knowledge from structured databases, documents, communication platforms, customer interactions, operational systems, and digital repositories. Conventional knowledge management approaches may face difficulties in organizing, retrieving, interpreting, and continuously updating such diverse information. Machine Learning (ML) provides intelligent techniques for discovering patterns, classifying information, recommending relevant knowledge, predicting knowledge requirements, and automating knowledge-related processes. This study examines machine learning techniques for advanced knowledge management and proposes a conceptual framework integrating knowledge acquisition, data preprocessing, representation, intelligent learning, knowledge discovery, recommendation, and continuous knowledge updating. A conceptual and descriptive research design is adopted through the synthesis of secondary scholarly literature related to machine learning, knowledge management, artificial intelligence, information retrieval, predictive analytics, and intelligent systems. The analysis indicates that supervised learning, unsupervised learning, natural language processing, recommendation models, deep learning, and anomaly detection can improve knowledge organization and accessibility. Machine learning can also support organizational learning by identifying hidden relationships and delivering contextually relevant information to users. However, challenges involving data quality, knowledge fragmentation, privacy, algorithmic bias, interpretability, cybersecurity, and model drift must be addressed. The study concludes that machine learning can strengthen advanced knowledge management when integrated with reliable information governance, human expertise, continuous learning, and responsible AI practices.
Keywords	Machine Learning, Knowledge Management, Intelligent Systems, Knowledge Discovery, Artificial Intelligence, Information Retrieval, Knowledge Sharing, Predictive Analytics, Organizational Intelligence
Field	Engineering
Published In	Volume 1, Issue 5, September-October 2019
Published On	2019-09-23

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American International Journal of Advanced Research and Development

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Machine Learning Techniques for Advanced Knowledge Management

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