Information Technology in Knowledge Management

Knowledge management is more a methodology applied to business practices than a technology or product. Nevertheless I.T is crucial to the secess of every KMS.

Components of Knowledge Management Systems:

1. Communication - Allow users to access needed knowledge and to communicate with each other
2. Collaboration
3. Storage and Retrieval - Involves capturing, storing, and managing tacit knowledge utilizing EDS.

Technologies Supporting Knowledge management:

• Artificial Intelligence
• Intelligent Agents - Software systems that learn how users work and provide assistance in their daily tasks. Intelligent agents can help in knowledge management (ibm.com), (gentia.com)
• Knowledge Discovery in Databases
• XML
• XBRL

AI methods:

• Expert Systems
• Neural Networks
• Fuzzy Logic
• Intelligent Agents

Are used in KMS to:

• Assist in and enhance searching knowledge
• Help establish knowledge profiles of individuals and groups
• Help determine the relative importance of knowledge when it is contributed to and accessed from the knowledge repository.
• Scan e-mail, documents, and databases to perform knowlede discovery, determine meaningful relationships, glean knowledge, or induce rules for expert systems.
• Identify patterns in data
• Forecast future results using existing knowledge.
• Provide advice directly from knowledge by using neural networks or expert systems.
• Provide a natural language or voice command-driven user interface for a knowledge management system.

Knowledge Discovery in Databases (KDD): a process used to search for and extract useful information from volumes of ducments and data. It includes tasks known as knowledge extraction, data archaeology, data exploration, data pattern processing, data dredging, and information harvesting All of these activities are automatically conducted and allow quick discovery of data stored in large databases, data warehouses, text documents, or knowledge repositories. Data Mining is the most prevalent form of KDD.