MIS INTELLIGENT INFORMATION SYSTEMS CHAPTER 13 Att and future

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1 MIS INTELLIGENT INFORMATION SYSTEMS CHAPTER 13 Att and future
Hossein BIDGOLI

2 Chapter 13 Intelligent Information Systems
l e a r n i n g o u t c o m e s 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.

3 l e a r n i n g o u t c o m e s (cont’d.)
Chapter 13 Intelligent Information Systems l e a r n i n g o u t c o m e s (cont’d.) 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.

4 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 ______________ and displaying knowledge and facts Capabilities of these systems have improved in an attempt to close the gap between artificial intelligence and human intelligence Att and future

5 AI Technologies Supporting Decision Making
Decision makers use information technologies in _____________-making analyses: What-is (TPS) What-if (DSS) Other questions: Why? What does it mean? What should be done? When should it be done?

6 Table 13.1 Applications of AI Technologies

7 Robotics 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

8 Expert Systems 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 ________________

9 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

10 Exhibit 13.1 An Expert System Configuration

11 Uses of Expert Systems Airline industry Forensics lab work
Banking and finance _________________________ Food industry Personal management Security US Government Agriculture

12 Criteria for Using Expert Systems
Human _____________ 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 Subject domain is limited Decision or task involves many rules and complex logic Scarcity of experts in the organization

13 Criteria for Not Using Expert Systems
Very few rules Too many rules Well-structured ______________ problems are involved Problems are in areas that are too wide and shallow Disagreement among experts Problems are solved better by human experts

14 Advantages of Expert Systems
Never becomes ______________, 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

15 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

16 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 DogPile Searches the Web by using several search engines Eliminates duplicate results

17 Personal Agents Agents perform specific tasks for a user Such as:
Remembering information for filling out Web forms Completing addresses after the first few characters are typed

18 Data-Mining Agents Work with a data _________________
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

19 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

20 Fuzzy Logic Allows a smooth, ________________ transition between human and computer vocabularies Designed to help computers simulate vagueness and uncertainty in common situations Used in: Search engines, chip design, database management systems, software development, and more Examples: Dryers Refrigerators Shower systems TVs Video camcorders

21 Artificial Neural Networks
Networks that learn and are capable of performing tasks that are difficult with conventional computers Examples: Playing ____________ Recognizing patterns in faces Used for poorly structured problems Uses patterns Instead of the “If-Then-Else” rules that expert Creates a model based on input and output

22 Exhibit 13.4 An Artificial Neural Network Configuration

23 Artificial Neural Networks (cont’d.)
Many companies are able to predict customers’ shopping behavior based on past purchases Used for many tasks, including: ________________ prediction Credit rating Investment analysis Oil and gas exploration Target marketing

24 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 ________________ of inputs that generates the most desirable outputs Techniques Selection or survival of the fittest Crossover Mutation

25 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 human However, progress has been steady

26 Table 13.2 NLP Systems

27 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

28 Summary Intelligent information systems Expert 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 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