Faculty of Arts Atkinson College ITEC 1010 A F 2002 Welcome Sixteenth Lecture for ITEC 1010 3.0 A Professor G.E. Denzel.

Faculty of ArtsAtkinson College

ITEC 1010 A F 2002

Welcome

Sixteenth Lecture for ITEC 1010 3.0 A

Professor G.E. Denzel


ITEC 1010 A F 2002

Agenda

Brief discussion of assignment q on changing background colour inline.

Finish Chapter 10 in text, dealing On-Line Analytical Processing (OLAP) and data-mining

Discussion of Artificial Intelligence approaches


ITEC 1010 A F 2002

Using Styles

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ITEC 1010 A F 2002

Analytical Processing - the activity of analyzing accumulated data

Online analytical processing (OLAP) An end-user activity Involves large data sets with complex

relationships Uses Decision Support Systems models Is retrospective

What can we do with the stored data?


ITEC 1010 A F 2002

Analysis by end users from their desktop, online, using tools like spreadsheets

Analyze the relationships between many types of business elements

Involve aggregated dataCompare aggregated data over hierarchical time

periods (monthly, quarterly, annually)Present data in different perspectivesInvolve complex calculations between data

elementsRespond quickly to users requests

Online Analytical Processing (OLAP)


ITEC 1010 A F 2002

Data mining – intelligent search of data stored in data marts or warehouses Find predictive information Discover unknown patterns

End users perform mining tasks with very powerful tools

Mining tools apply advanced computing techniques (learning, intelligence)

What can we do with the stored data?


ITEC 1010 A F 2002

Ethical Issues Valuable data-mined information may violate individual

privacy Who is accountable for incorrect decisions that are based

on DSS? Human judgment is fallible Job loss due to automated decision making?

Legal Issues Discrimination based on data mining results Data security from external snooping or sabotage Data ownership of personal data

Data Mining and Analysis Concerns


ITEC 1010 A F 2002

Chapter PreviewIn this chapter, we will study:

What is meant by artificial intelligence How expert systems are developed and how they

perform How AI has been applied to other arenas, such as

natural language processing and neural computing

The concept and usefulness of intelligent agents Ethical and legal issues posed by AI


ITEC 1010 A F 2002

‘Intelligent’ Systems? Conventional computer systems do not

possess ‘intelligence.’ They simply follow step-by-step instructions to complete a task

If a computer system had ‘intelligence,’ it would… Deal successfully with complex situations Learn from experience Adapt to new situations quickly


ITEC 1010 A F 2002

Why do we want ‘Intelligent’ Systems?

To capture and represent human knowledge permanently

To perform tasks requiring intelligence repetitively, consistently, and capably

To document the performance of a task To conveniently disseminate knowledge

and expertise to others


ITEC 1010 A F 2002

Artificial Intelligence Branch of computer science that

Studies human intelligent behavior Attempts to replicate that human intelligent

behavior in a computer system Employs symbolic processing of

knowledge and heuristics Does not really enable computers to ‘think’ Does enable creation of systems with some

human-like behaviors


ITEC 1010 A F 2002

Applications of Artificial Intelligence

Expert Systems Natural language

technology Speech

understanding Robotics Computer vision

Intelligent computer-assisted instruction

Machine learning Handwriting

recognition Intelligent agents


ITEC 1010 A F 2002

What is an Expert System? Computer system that solves a problem as

successfully as a human expert Incorporates human expertise Acquires facts about the problem Applies its stored knowledge and expertise

to the problem facts to derive a solution Makes recommendations Can explain its reasoning and logic Successful commercial application of AI


ITEC 1010 A F 2002

Key Expert System Terms Knowledge acquisition – the process of

obtaining knowledge and expertise from human experts

Knowledge representation – the method used to represent human knowledge and expertise in the computer system

Knowledge inferencing – the process of applying stored expertise to the facts about the problem to draw conclusions

Knowledge transfer and use – the communication of the problem solution and its justification to the system user


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More Expert System Terms Knowledge base – stored facts and methods of how to

solve a problem Heuristic – rule of thumb that can be applied in a

problem solution Inference engine – processing logic stored in the system

that correctly applies the stored knowledge to the problem to develop a solution

Domain expert – one or more humans who have achieved a high level of expertise in solving a problem

Knowledge engineer – person who develops expert systems


ITEC 1010 A F 2002

How is an Expert System Created?

Knowledge engineer works with domain expert to extract domain knowledge

Knowledge engineer encodes domain knowledge in knowledge base using appropriate knowledge representation

Knowledge engineer tests system on sample problems and refines system knowledge with help from domain engineer

Refinement continues until system is solving problems with human expert capability


ITEC 1010 A F 2002

How Does an Expert System Perform?

System asks user a series of questions to gather facts about the problem

System uses inference engine to form conclusions from the facts, including a measure of certainty about the conclusions

System displays its recommendation or solution to the problem

If asked, the system can display its reasoning and logic as to how it arrived at the conclusion


ITEC 1010 A F 2002

Inferenceengine

Explanationfacility

Knowledgebase

acquisitionfacility

Userinterface

Knowledgebase

Experts User


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Expert System Structure


ITEC 1010 A F 2002

More on Expert Systems Strengths

Rapid, consistent problem solutions

Ability to justify and explain reasoning

Easy to replicate and distribute to non-expert users

Limitations Can only solve

problems in a narrow domain

Can only be applied to certain problem types

Cannot learn from its experience

Hard to acquire knowledge from human expert


ITEC 1010 A F 2002

Other Intelligent Systems Natural Language Processing

The ability to communicate with a computer in your natural language• Voice (speech) recognition and speech

understanding – system recognizes spoken words and understands their meaning

• Voice synthesis – computer produces natural language voice output that sounds ‘human’


ITEC 1010 A F 2002

Other Intelligent Systems Neural Computing

A computer model that uses architecture that mimics certain brain functions

Performs pattern recognition well Can analyse large data sets and discover

patterns where rules were previously unknown Can ‘learn’ by analysing new cases and

updating itself Many potential business applications


ITEC 1010 A F 2002

Figure 11.2 Neural Internet-based optical character recognizer.


ITEC 1010 A F 2002

More Neural Nets

Discussion of using Neural networks to predict the stockmarket --- why not?


ITEC 1010 A F 2002

Other Intelligent Systems Case-Based Reasoning

Uses solutions from similar problems and adapts them to new problems

Useful in solving very complex cases Fuzzy Logic

Enables systems to effectively deal with uncertainty

Often use in combination with other technologies to improve productivity


ITEC 1010 A F 2002

Rules for a Credit Application (Could be from neural net or expert system)

Mortgage application for a loan for $100,000 to $200,000

If there are no previous credits problems, and

If month net income is greater than 4x monthly loan payment, and

If down payment is 15% of total value of property, and

If net income of borrower is > $25,000, and

If employment is > 3 years at same company

Then accept the applications

Else check other credit rules


ITEC 1010 A F 2002

Intelligent Agents Software agent that autonomously performs

tasks on behalf of a user with certain goals or objectives Can tirelessly perform repetitive tasks over a

network Includes knowledge base and ability to learn Can be static (on the client only) or mobile

(move throughout a network) Often used to facilitate search and retrieval on

the Internet and to assist in e-commerce tasks


ITEC 1010 A F 2002

Examples of Agents in use today

Search engines (yahoo, alta vista, ask Jeeves, etc.)

Stock trackers http://www.botspot.com


ITEC 1010 A F 2002

Virtual Reality Simulation of a physical environment in a

highly realistic way Useful for communication and learning Many potential business applications,

especially marketing


ITEC 1010 A F 2002

Intelligent Systems Concerns Potential to use the power of intelligent

systems in unethical ways Who will be accountable for decisions

made by intelligent systems? Who ‘owns’ knowledge and expertise?

Can an expert be ‘forced’ to reveal his/her expertise?

Faculty of Arts Atkinson College ITEC 1010 A F 2002 Welcome Sixteenth Lecture for ITEC 1010 3.0 A Professor G.E. Denzel.

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