1 MIS, Chapter 13 ©2011 Course Technology, a part of Cengage Learning INTELLIGENT INFORMATION SYSTEMS CHAPTER 13 Hossein BIDGOLI MIS

1MIS, Chapter 13

©2011 Course Technology, a part of Cengage Learning

INTELLIGENT INFORMATION SYSTEMS

CHAPTER 13

Hossein BIDGOLI

MIS

2MIS, Chapter 13


Chapter 13 Intelligent Information Systems

LO1 Define artificial intelligence and explain how these technologies support decision making.

LO2 Explain an expert system, its applications, and its components.

LO3 Describe case-based reasoning.

LO4 Summarize types of intelligent agents and how they’re used.

LO5 Describe fuzzy logic and its uses.

l e a r n i n g o u t c o m e s

3MIS, Chapter 13


LO6 Explain artificial neural networks.

LO7 Describe how genetic algorithms are used.

LO8 Explain natural language processing and its advantages and disadvantages.

LO9 Summarize the advantages of integrating AI technologies into decision support systems.

l e a r n i n g o u t c o m e s (cont’d.)


4MIS, Chapter 13



What Is Artificial Intelligence?

• Artificial intelligence (AI) – Consists of related technologies that try to

simulate and reproduce human thought and behavior

– Includes thinking, speaking, feeling, and reasoning

• AI technologies – Concerned with generating and displaying

knowledge and facts

5MIS, Chapter 13



What Is Artificial Intelligence? (cont’d.)

• Knowledge engineers try to discover “rules of thumb” – Enable computers to perform tasks usually

handled by humans

• Capabilities of these systems have improved in an attempt to close the gap between artificial intelligence and human intelligence

6MIS, Chapter 13



AI Technologies Supporting Decision Making

• Decision makers use information technologies in decision-making analyses:– What-is– What-if

• Other questions:– Why? – What does it mean? – What should be done? – When should it be done?

7MIS, Chapter 13


Table 13.1 Applications of AI Technologies

8MIS, Chapter 13



Robotics

• Some of the most successful applications of AI

• Perform well at simple, repetitive tasks• Currently used mainly on assembly lines in

Japan and the United States• Cost of industrial robots• Some robots have limited vision

9MIS, Chapter 13



Robotics (cont’d.)

• Honda’s ASIMO– One of the most advanced and most popular

robots– Works with other robots in coordination

• Personal robots– Mobility, limited vision, and some speech

capabilities

• Robots have some unique advantages in the workplace compared with humans

10MIS, Chapter 13



Expert Systems

• One of the most successful AI-related technologies

• Mimic human expertise in a field to solve a problem in a well-defined area

• Consist of programs that mimic human thought behavior – In a specific area that human experts have

solved successfully

• Work with heuristics

11MIS, Chapter 13



Components of an Expert System

• Knowledge acquisition facility• Knowledge base• Factual knowledge• Heuristic knowledge• Meta-knowledge• Knowledge base management system

(KBMS)• Explanation facility• Inference engine

12MIS, Chapter 13


Exhibit 13.1 An Expert System Configuration

13MIS, Chapter 13



Components of an Expert System (cont’d.)

• Forward chaining– Series of “If-Then-Else”– Condition pairs are performed

• “If” condition is evaluated first• Then the corresponding “Then-Else” action

is carried out

• Backward chaining– Starts with the goal first—the Then part– Backtracks to find the right solution

14MIS, Chapter 13



Components of an Expert System (cont’d.)

• Semantic (associative) networks– Represent information as links and nodes

• Frames – Store conditions or objects in hierarchical order

• Scripts – Describe a sequence of events

15MIS, Chapter 13



Uses of Expert Systems

• Airline industry• Forensics lab work• Banking and finance• Education• Food industry• Personal management• Security• US Government• Agriculture

16MIS, Chapter 13



Expert Systems in Baltimore County Police Department

•In Baltimore County, an expert system was developed so that detectives could analyze information about burglary sites and identify possible suspects

•Detectives could enter statements about burglaries, such as neighborhood characteristics, the type of property stolen, and the type of entry used; they could also get information on possible suspects

17MIS, Chapter 13



Criteria for Using Expert Systems

• Human expertise is needed but one expert can’t investigate all the dimensions of a problem

• Knowledge can be represented as rules or heuristics

• Decision or task has already been handled successfully by human experts

• Decision or task requires consistency and standardization

18MIS, Chapter 13



Criteria for Using Expert Systems (cont’d.)

• Subject domain is limited• Decision or task involves many rules and

complex logic• Scarcity of experts in the organization

19MIS, Chapter 13



Criteria for Not Using Expert Systems

• Very few rules• Too many rules• Well-structured numerical problems are

involved• Problems are in areas that are too wide

and shallow• Disagreement among experts• Problems are solved better by human

experts

20MIS, Chapter 13



Advantages of Expert Systems

• Never becomes distracted, forgetful, or tired

• Duplicates and preserves the expertise of scarce experts

• Preserve the expertise of employees who are retiring or leaving an organization

• Creates consistency in decision making• Improves the decision-making skills of

nonexperts

21MIS, Chapter 13



Case-Based Reasoning

• Problem-solving technique• Matches a new case (problem) with a

previously solved case and its solution stored in a database

• If there’s no exact match between the new case and cases stored in the database: – System can query the user for clarification or

more information

• If still no match found: – Human expert must solve the problem

22MIS, Chapter 13



Intelligent Agents

• Bots (short for robots)• Applications of artificial intelligence are

becoming more popular– Particularly in e-commerce

• Consist of software capable of reasoning and following rule-based processes

23MIS, Chapter 13



Intelligent Agents (cont’d.)

• Characteristics:– Adaptability– Autonomy– Collaborative behavior– Human-like interface– Mobility– Reactivity

24MIS, Chapter 13



Intelligent Agents (cont’d.)

• Web marketing– Collects information about customers, such as

items purchased, demographic information, and expressed and implied preferences

• “Virtual catalogs” – Display product descriptions based on

customers’ previous experiences and preferences

25MIS, Chapter 13



Shopping and Information Agents

• Help users navigate through the vast resources available on the Web

• Provide better results in finding information• Examples:

– PriceScan– BestBookBuys.com– www.mysimon.com– DogPile

• Searches the Web by using several search engines

• Eliminates duplicate results

26MIS, Chapter 13



Personal Agents

• Agents perform specific tasks for a user• Such as:

– Remembering information for filling out Web forms

– Completing e-mail addresses after the first few characters are typed

27MIS, Chapter 13



Data-Mining Agents

• Work with a data warehouse• Detect trend changes• Discover new information and

relationships among data items that aren’t readily apparent

• Having this information early enables decision makers to come up with a solution that minimizes the negative effects of the problem

28MIS, Chapter 13



Monitoring and Surveillance Agents

• Track and report on computer equipment and network systems– To predict when a system crash or failure might

occur

• Example: NASA’s Jet Propulsion Laboratory

29MIS, Chapter 13



Fuzzy Logic

• Allows a smooth, gradual transition between human and computer vocabularies

• Deals with variations in linguistic terms by using a degree of membership

• Designed to help computers simulate vagueness and uncertainty in common situations

• Works based on the degree of membership in a set

30MIS, Chapter 13


Exhibit 13.3 Degree of Membership in a Fuzzy System

31MIS, Chapter 13



Uses of Fuzzy Logic

• Used in:– Search engines, chip design, database

management systems, software development, and more

• Examples:– Dryers– Refrigerators– Shower systems– TVs– Video camcorders

32MIS, Chapter 13



Artificial Neural Networks

• Networks that learn and are capable of performing tasks that are difficult with conventional computers

• Examples:– Playing chess– Recognizing patterns in faces

• Used for poorly structured problems• Use patterns instead of the “If-Then-Else”

rules that expert systems use• Create a model based on input and output

33MIS, Chapter 13


Exhibit 13.4 An Artificial Neural Network Configuration

34MIS, Chapter 13



Artificial Neural Networks (cont’d.)

• Used for many tasks, including:– Bankruptcy prediction– Credit rating– Investment analysis– Oil and gas exploration– Target marketing

35MIS, Chapter 13



Neural Networks in Action

• Many companies are able to predict customers’ shopping behavior based on past purchases

• E-banks use neural networks to rank their customers into groups

• Visa International – Introduced a credit authorization system based

on neural networks to reduce credit card fraud – Could cut fraudulent transactions by as much

as 40%

36MIS, Chapter 13



Genetic Algorithms

• Used mostly in techniques to find solutions to optimization and search problems

• Applications:– Jet engine design, portfolio development, and

network design

• Find the combination of inputs that generates the most desirable outputs

• Techniques:– Selection or survival of the fittest– Crossover– Mutation

37MIS, Chapter 13



Natural Language Processing

• Developed so that users can communicate with computers in their own language

• Provides question-and-answer setting that’s more natural and easier for people to use

• Products aren’t capable of a dialogue that compares with conversations between humans– However, progress has been steady

38MIS, Chapter 13


Table 13.2 NLP Systems

39MIS, Chapter 13



Natural Language Processing (cont’d.)

• Categories:– Interface to databases– Machine translation– Text scanning and intelligent indexing

programs for summarizing large amounts of text

– Generating text for automated production of standard documents

– Speech systems for voice interaction with computers

40MIS, Chapter 13



Natural Language Processing (cont’d.)

• Interfacing – Accepting human language as input– Carrying out the corresponding command– Generating the necessary output

• Knowledge acquisition– Using the computer to read large amounts of

text and understand the information well enough to:• Summarize important points and store

information so that the system can respond to inquiries about the content

41MIS, Chapter 13



Integrating AI Technologies into Decision Support Systems

• I-related technologies can improve the quality of decision support systems (DSSs)– Including expert systems, natural language

processing, and artificial neural networks

• Benefits of integrating an expert system into the database component of a DSS are:– Adding deductive reasoning to traditional

DBMS functions– Improving access speed

42MIS, Chapter 13



Summary

• Intelligent information systems– AI technologies are used to support decision-

making processes

• Expert systems– Components

• Case-based reasoning• Intelligent agents• Fuzzy logic and genetic algorithms• Natural language processing

Documents

1 MIS, Chapter 13 ©2011 Course Technology, a part of Cengage Learning INTELLIGENT INFORMATION SYSTEMS CHAPTER 13 Hossein BIDGOLI MIS