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Knowledge Engineering (Wissensverarbeitung)

L.048.23014

Handouts : http://adt.upb.de (dann "Lehre")

Prof. Dr. F. Belli Universität Paderborn,

Fakultät EIM, Institut für Elektrotechnik und Informationstechnik

Angewandte Datentechnik (Softwaretechnik)

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0. What is Knowledge?

Webster’s New Encyclopaedic Dictionary

Data:

factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation

Information:

1. the communication or reception of knowledge or intelligence

2. a) knowledge obtained from investigation, study, or instruction

2. b) knowledge of a particular event or situation (news)

2. c) fact, data

2. d) a signal or mark put into or put out by a computing machine Knowledge:

1. understanding gained by actual experience

2. a) the state of being aware of something or of having information

2 b) range of awareness or information

3. the act of understanding: clear perception of truth

4. something learnt and kept in mind

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0. What is Knowledge?

Davenport & Prusak, 1998:

Data:

– Data is a set of discrete, objective facts about events. In an organizational context, data is most usefully described as structured records of transactions. Data by itself has little relevance or purpose.

Information:

– Information is a message, usually in the form of a document or an audible or visible communication. Information is meant to change the way the receiver perceives

something, to have an impact on his judgment and behavior. It must inform; it s data that makes a difference.

Knowledge:

– Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new

experiences and information. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and

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Programming Paradigms

imperative

machine-oriented (Assembler)

procedural (Pascal, C)

object-oriented (C++, Java)

declarative

functional (LISP)

logic-based (Prolog)

rule-based (OPS 5)

Paradigms

1st Sem. B.Sc.

4/6th Sem. B.Sc.

M.Sc.

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About the course L.048.23014:

Weekly date: on Fridays, 9:30a.m. – 12:30p.m.

Password: wv-$u$e!3

Objective: A basic, hands-on introduction to knowledge engineering

ƒ In the large: Problem solving and generating new knowledge from existing ones.

ƒ In the small: Notions (terminology, methods, and

techniques) for organization and realization of knowledge- based systems.

ƒ How: e.g. with PROLOG (PROgramming in LOGic) for

acquisition, representation, and processing of knowledge.

ƒ Focus on problem solving in conjunction with fault

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Text Books:

[1] F. Belli, Einführung in die logische Programmierung mit PROLOG, BI Wissenschaftsverlag, 1986

[2] I. Boersch, J. Heinsohn, R. Socher, Wissensverarbeitung. Eine Einführung in die Künstliche Intelligenz für Informatiker und

Ingenieure, Spektrum Akademischer Verlag, 2007

[3] I. S. Kendal, M. Creen, An Introduction to Knowledge Engineering, Springer, 2006

<http://www.springerlink.com/content/978-1-84628-475-5/contents>

Reference Book:

[ 4] S.J. Russell, P. Norvig, Artificial Intelligence: A Modern

Approach, Prentice Hall

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Content

1. Introduction –

Data-Based Systems (DBS) and

Knowledge-Based Systems/Expert Systems (KBS/XS) 2. PROLOG for Knowledge Representation (KR) /

Processing (KP) – Introduction

3. Representing Vague Knowledge – Fuzzy Logic 4. Artificial Neural Networks

5. Testing

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• Any Questions or Wishes ?

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