Fundamentals chapter 9 Flashcards
Knowledge Management and Specialized Information Systems
Knowledge management
Can be defined as awareness and understanding of a set of information and ways that information can be made useful to support a specific task or reach a decision.
Information – tells you what needs to be done
Knowledge – how to do it
knowledge Management System (KMS)
is an organized collection of people, procedures, software, databases and devices used to create, store, share and use the organization’s knowledge and experience.
Types of knowledge:
Explicit knowledge – objective knowledge that can be measured and documented
Tacit knowledge – knowledge based on skill and experience of various situations, which is difficult to measure and document
Four ways in which knowledge can be created
1.When an individual learns directly from another individual
2.When two pieces of explicit knowledge are combined
3.When an expert writes a book teaching others
4.When someone reads that book and becomes an expert themselves
Knowledge Workers
These are people who create, use and disseminate knowledge.
They are usually professionals from fields such as:
Science
Engineering
Business
Literature
Research
Education
Chief Knowledge Officer (CKO)
a top level executive who is responsible for the creation, storage and use of knowledge to achieve organizational goals
Some types of software can store and share knowledge:
PDF
Spreadsheets (e.g. Excel)
Group support applications (Application with workgroup and enterprise sphere of influence – Chapter 2)
There are more robust systems that can be use for knowledge management:
Databases
Data Warehouses
Expert Systems
Enterprise Resource Planning Systems (ERPs)
Business Intelligence Systems (BI)
Artificial intelligence
This term refers to computers that mimic or duplicate the functions of the human brain i.e. intelligent behavior
Artificial Intelligence systems include the people, procedures, hardware, software, data, and knowledge needed to demonstrate characteristics of intelligence
AI Characteristics
Learn from experience and apply the knowledge acquired from experience
Handle complex situations
Solve problems when important information is missing
Determine what is important
React quickly and correctly to a new situation
Understand visual images
Process and manipulate symbols
Be creative and imaginative
Use heuristics
Major branches of artificial intelligence
Expert Systems
Robotics
Vision Systems
Natural Language Processing and Voice Recognition
Learning Systems
Neural Networks
Expert Systems
A type of system that outputs a recommendation based on answers given to it by users who are experts in their field.
The intention of such a system is to capture and ‘posses’ the knowledge of an expert, and make it available to users who need it when required.
Some application fields include:
Medicine
Engineering
Energy
Product design and development (e.g. industrial design)
Uses Heuristics
What can Expert system do
1.Provide a high potential payoff or significantly reduce downside risk
2.Capture and preserve irreplaceable human expertise
3.Solve a problem that is not easily solved using traditional programming techniques
4.Develop a system which is more consistent than human experts
5.Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health
6.Provide expertise that is expensive or rare
7.Develop a solution faster than human experts can
8.Provide expertise needed for training and development to share the wisdom and experience of human experts with many people
Some examples of application/use of Artificial Intelligence and Expert Systems
Credit granting and loan analysis
Stock picking
Catching cheats and terrorists
Budgeting
Games
Plant layout and manufacturing
High level languages that were traditionally used to program such systems are:
Pascal
FORTRAN
COBOL
