Chapter 11
What is the knowledge creation and management value chain in organizations? How can IS assist in this process?
Knowledge work systems (KWS) support the creation of new knowledge and its integration into the organization. KWS require easy access to an external knowledge base; powerful computer hard-ware that can support software with intensive graphics, analysis, document management, and communications capabilities; and a user-friendly interface. KWS include computer-aided design (CAD) systems, augmented reality applications, and virtual reality systems, which create interactive simulations that behave like the real world, with intensive graphics and powerful modeling capabilities.
Machine Learning
Leverages massive amounts of data so that computers can act and improve on their own without additional programming.
What is the difference between supervised learning and unsupervised learning?
Supervised learning is a human aided effort that works to implement inputs into a computer with a compiled network in order that the computer may learn inputs overtime, where as unsupervised learning is a collection of networks that serve to mimic the human brain and in theory are able to learn unsupervised by humans.
Robotics
Technology dealing with the design, construction, and operation of robots in automation.
Expert Systems
computer programs that help people solve technical problems
Understand and differentiate among the Enterprise-wide knowledge management systems, Intelligent techniques and Knowledge work systems
knowledge management systems are general-purpose firmwide efforts to collect, store, distribute, and apply digital content and knowledge. These systems include capabilities for searching for information, storing both structured and unstructured data, and locating employee exper-tise within the firm. They also include supporting technologies such as portals, search engines, collaboration and social business tools, and learning manage-ment systems. "intelligent" techniques, such as data mining, expert systems, machine learning, neural net-works, natural language processing, computer vision systems, robotics, genetic algorithms, and intelligent agents. These techniques have different objectives, from a focus on discovering knowledge (data mining and neural networks) to dis-tilling knowledge in the form of rules for a computer program (expert systems) to discovering optimal solutions for problems (genetic algorithms). Knowledge work systems (KWS) are specialized systems built for engineers, scientists, and other knowl-edge workers charged with discovering and creating new knowledge for a com-pany. W
natural language processing
processing that allows the computer to understand and react to statements and commands made in a "natural" language, such as English
Genetic Algorithms (GAs)
search algorithms that mimic the process of natural evolution. They are used to generate solutions to optimization and search problems using such techniques as mutation, selection, crossover, and chromosome.
Intelligent agents
sophisticated software programs that use collaborative filtering technologies cto learn from past user behavior in order to recommend new purchases
