Enhancing Knowledge Management Systems through Data Mining Integration

Abstract

Knowledge Management Systems (KMS) are essential in organizations for organizing, storing, and distributing knowledge to improve decision-making and foster innovation. However, the effectiveness of KMS is often limited by the inability to process vast amounts of unstructured data, which often results in underutilization of available knowledge. This research paper explores how integrating Data Mining (DM) techniques can enhance KMS by enabling the automatic extraction of valuable insights from data, optimizing knowledge retrieval, and improving decision-making processes. The paper provides a comprehensive review of existing KMS, outlines methodologies for integrating DM, and presents results from case studies in various industries. A comparison of pre- and post-integration performance highlights the significant improvements achieved through this integration. The findings demonstrate that integrating Data Mining into KMS can not only improve knowledge discovery but also contribute to better business outcomes by improving the relevance and efficiency of knowledge retrieval.