1. 11 Chapter Managing Knowledge

5. U.S. Enterprise Knowledge Management Software Revenues, 2001-2008 Figure 11-1 Enterprise knowledge management software includes sales of content management and portal licenses, which have been growing at a rate of 35 percent annually, making it among the fastest-growing software applications. The Knowledge Management Landscape Management Information Systems Chapter 11 Managing Knowledge

13. The Knowledge Management Value Chain Figure 11-2 Knowledge management today involves both information systems activities and a host of enabling management and organizational activities. The Knowledge Management Landscape Management Information Systems Chapter 11 Managing Knowledge

16. Major Types of Knowledge Management Systems Figure 11-3 There are three major categories of knowledge management systems, and each can be broken down further into more specialized types of knowledge management systems. The Knowledge Management Landscape Management Information Systems Chapter 11 Managing Knowledge

18. Enterprise-Wide Knowledge Management Systems Figure 11-4 Enterprise-wide knowledge management systems use an array of technologies for storing structured and unstructured documents, locating employee expertise, searching for information, disseminating knowledge, and using data from enterprise applications and other key corporate systems. Enterprise-Wide Knowledge Management Systems Management Information Systems Chapter 11 Managing Knowledge

21. K-World’s Knowledge Domains Figure 11-5 KPMG’s KWorld is organized into nine levels of content that are further classified by product, market segment, and geographic area. Enterprise-Wide Knowledge Management Systems Management Information Systems Chapter 11 Managing Knowledge

24. LiveLink ECM-eDOCS’ Integrated Knowledge Management System Figure 11-6 Open Text’s Livelink ECM-eDOCS enterprise solution combines document management, knowledge management, business intelligence, and portal technologies and can be used for managing semistructured as well as structured knowledge. Enterprise-Wide Knowledge Management Systems Management Information Systems Chapter 11 Managing Knowledge

28. AskMe Enterprise Knowledge Network System Figure 11-7 A knowledge network maintains a database of firm experts, as well as accepted solutions to known problems. The system facilitates the communication between employees looking for knowledge and internal solution providers, either through the Web-based system, standard e-mail such as Outlook, or instant messaging solutions or handheld devices. Solutions created in this communication are then added to a database of solutions in the form of FAQs, best practices, or other documents. Enterprise-Wide Knowledge Management Systems Management Information Systems Chapter 11 Managing Knowledge

34. Requirements of Knowledge Work Systems Figure 11-8 Knowledge work systems require strong links to external knowledge bases in addition to specialized hardware and software. Knowledge Work Systems Management Information Systems Chapter 11 Managing Knowledge

39. Rules in an Expert System Figure 11-9 An expert system contains a number of rules to be followed. The rules are interconnected; the number of outcomes is known in advance and is limited; there are multiple paths to the same outcome; and the system can consider multiple rules at a single time. The rules illustrated are for simple credit-granting expert systems. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

40. Inference Engines in Expert Systems Figure 11-10 An inference engine works by searching through the rules and “firing” those rules that are triggered by facts gathered and entered by the user. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

43. How Case-Based Reasoning Works Figure 11-11 Case-based reasoning represents knowledge as a database of past cases and their solutions. The system uses a six-step process to generate solutions to new problems encountered by the user. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

45. Implementing Fuzzy Logic Rules in Hardware Figure 11-12 The membership functions for the input called temperature are in the logic of the thermostat to control the room temperature. Membership functions help translate linguistic expressions such as warm into numbers that the computer can manipulate. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

47. How a Neural Network Works Figure 11-13 A neural network uses rules it “learns” from patterns in data to construct a hidden layer of logic. The hidden layer then processes inputs, classifying them based on the experience of the model. In this example, the neural network has been trained to distinguish between valid and fraudulent credit card purchases. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

49. The Components of a Genetic Algorithm Figure 11-14 This example illustrates an initial population of “chromosomes,” each representing a different solution. The genetic algorithm uses an iterative process to refine the initial solutions so that the better ones, those with the higher fitness, are more likely to emerge as the best solution. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge

52. Intelligent Agents in P&G’s Supply Chain Network Figure 11-15 Intelligent agents are helping Procter & Gamble shorten the replenishment cycles for products such as a box of Tide. Intelligent Techniques Management Information Systems Chapter 11 Managing Knowledge