KNOWLEDGE-BASED SYSTEM

Riego TamanioLorenzo AmoresMarc TibayanRemuel Lepatan

Introduction

Knowledge-based Information Systems

Also known as ‘KBS’ Use reasons and human-based

knowledge 3 components

Set of interfaces Inference engine Knowledge base

Knowledge-based System

History

General problem solving during the late 50’s and early 60’s

Markov Algorithm (1954) DENDRAL (First Expert System)

(1965) MYCIN (1972-73) META-DENDRAL (1978) RETE algorithm (developed by

Charles R. Foggy)(1979)

History

Knowledge-Based Systems were recognized as a practical tool or solving real-world problems (1980’s)

A new specialized hardware was developed, optimized to run expert system software fast (1980)

Social Impact and Relevance KBS are widely used in different natures of

work management Quickly answers for expert consultation Answers too complex problems Through the use of this kind of systems,

many types of industries have been set to have successful and more efficient operations.

Some are designed to take the place of human experts, while others are designed to assist them.

Advancement Concept

Better time span process. Can process loads of information a

lot faster than the human brain. Knowledge-based System shows the

success of mankind in the field of Computer.

Application and Benefits

Knowledge-based Systems provide a wide range of benefits for people, whether professional or non-professional.

Can be experts in a narrow and specific field of study and intelligence

Can also be helpful on all fields depending on its Knowledge-base.

Knowledge-based systems are particularly good at making critical decisions that we, humans, might not be making

Industries that uses the Technology

Banking systems for processing loan applications, journey planners and

Timetable Schedulers for travel firms Visual Units used in robotics in the manufacturing

sectors of industry. Manufacturing Systems which help in the total

manufacturing process Financial systems Commercial and Industrial Settings

Medicine Finance Manufacturing Sales

Future Trends

Developers foresee Knowledge-based Systems that will: Be Able to solve difficult problems as well as or better

than human experts Reason inquisitively using very effective heuristics Interact with humans in appropriate ways, including

natural languages Manipulate and reason about symbolic descriptions Function with data that contains errors, using certain

judgmental rules and Can contemplate multiple competing assumptions

simultaneously Be able to explain why they are asking a question and

justify their answers.

Conclusion

Knowledge-based Systems are systems that can provide narrow intelligent decisions with justification.

3 components Set of interfaces Inference engine Knowledge base

They can be helpful to professionals like doctors, nurses, architects, etc. The said system has been and is continuously being developed for other professions and purposes.