Ch 7 - Knowledge Management and Specialized Information Systems 

Knowledge Management Systems recap: Data consists of raw facts

Information: collection of facts organised so they have additional value beyond the facts themselves

Knowledge: awareness and understanding of a set of information and the ways that information can be made useful to support a specific task or reach a decision

Knowledge Management Systems (KMS): is an organised collection of people, procedures, software, databases, and devices.

• Used to create, store, share, and use the organisation’s knowledge and experience

Explicit Knowledge: is objective, can be measured and documented in reports, papers, and rulers

Tacit Knowledge: hard to measure and document, typically not objective or formalised

Data and Knowledge Management workers:

• Data workers: secretaries, administrative assistants, bookkeepers
• Knowledge workers: create, use, and disseminate knowledge

Chief Knowledge Officer (CKO): top-level executive who helps the organisation use a KMS to create, store, and use knowledge to achieve organisational goals

Communities of Practice (COP): group of people dedicated to a common discipline or practice. May be used to create, store, and share knowledge

• Knowledge repository: includes documents, reports, files and databases
• Knowledge map: directory that points the knowledge worker to the needed knowledge
• Effective KMS: is based on learning new knowledge and changing procedure and approaches as a result

Overview on Artificial Intelligence:

• Artificial Intelligence: computers with the ability to mimic or duplicate the functions of the human brain
• Artificial intelligence systems: include the people, procedures, hardware, software, data, and knowledge needed to develop computer systems and machines that demonstrate characteristics of human intelligence
• Turing Test: determines whether responses from a computer with high intelligence are distinguishable from a human being

Characteristics of Artificial Intelligence:

• Determine key factors
• React quickly and correctly to new situation
• Understand visual imagine
• Process and manipulate symbols
• Creative and imaginative

Brain Computer Interface:

• Brain computer interface (BCI): idea is to directly connect the human brain to a computer and have thought control computer activities

• The BCI experiment will allow people to control computers and artificial arms and legs through thought alone

  • AI includes:
  • Expert systems and robotics
  • Vision systems and natural language processing
  • Learning systems and neural networks

• Expert systems: hardware and software that stores knowledge and makes inferences, similar to human expert

• Consists of a collection of integrated and related components

• Robotics: mechanical devices that can perform tasks that require a high degree of precision

• Manufacturers use robots to assemble and paint products

• Contemporary robotics: combine both high precision machine capabilities and sophisticated controlling software

Vision Systems: Hardware and software that permit computers to capture, store, and manipulate visual images and pictures

• Effective at identifying people based on facial features

Natural language processing: processing that allows the computer to understand and react to statements and commands made in a “natural” language

Voice recognition: converting sound waves into words

Learning systems: combination of software and hardware that allows the computer to change how it functions or reacts to situations based on feedback it receives

Learning systems software: requires feedback on results of actions or decisions

Neural Networks: computer system that simulates functioning of a human brain

• Can process many pieces of data at the same time
• Neural network program: helps engineers slow or speed drilling operations to help increase accuracy/reduce costs

Genetic Algorithm: approach to solving complex problems in which a number of related operations or models change and evolve until the best one emerges

Intelligent Agent: programs and a knowledge base used to perform a specific task for a person, process, or another program

Computerised expert systems: systems that use heuristics (techniques) to arrive at conclusions or make suggestions

• Expert systems should be introduced in organisations if it can:
• High payoff/reduce risk
• Capture and preserve irreplaceable expertise
• Solve a problem not easily solved using traditional programming techniques
• More consistent system than human experts

Components of Expert System:

• Knowledge base: stores all relevant information, data, rules, cases, and relationship used by expert system
• Created by using rules and cases

Inference Engine: seeks information and relationships from the knowledge base

• Provides answers, predictions, and suggestions like a human expert

Explanation Facility: allows user or decision maker to understand how the expert system arrived at certain conclusions or results

Knowledge Acquisition facility: provides convenient and efficient means of capturing and string all components of knowledge base

Knowledge acquisition software:

• Can present users and decision makers with easy to use menus

User Interface: permits decision makers to develop and use their own expert systems

• Main purpose: to make development and use of an expert system easier for users and decision makers

Participants in developing and Using Expert Systems:

• Domain Expert: person or group with the expertise or knowledge the expert system is trying to capture
• Knowledge engineer: person who has training in the design, development, implementation, and maintenance of an expert system
• Knowledge user: person or group who uses and benefits from the expert system
• Expert systems can be developed from any programming language
• Expert system shells and products: collections of software packages and tools used to design, develop, implement, and maintain expert systems

Multimedia and Virtual Reality:

• They have helped many companies achieve a competitive advantage ad increase profits. The approach and technology used in multimedia is often the foundation of virtual reality systems
• Multimedia is:
• Text and graphics
• Audio
• Video and animation

Virtual reality system: enables one or more users to move and react in a computer-simulated environment

Immersive virtual reality: user becomes fully immersed in an artificial, 3D world that is completely generated by a computer \n

Interface devices:

• Haptic interface: relays sense of touch and other sensations in a virtual world
• Most challenging to create

Specialised systems:

• Game theory: uses information systems to develop competitive strategies for people, organisations, or even countries
• Informatics: combines traditional disciplines, such as science and medicine, with computer systems and technology