Expert Systems for IT Students

What are the main knowledge representation techniques used in expert systems?

• Genetic algorithms

• Production rules, semantic networks, frames, ontologies

• Neural networks

• Decision trees

How do expert systems assist in decision support processes?

• Expert systems only store data without providing insights.

• Expert systems are primarily used for hardware maintenance.

• Expert systems replace human decision-makers entirely.

• Expert systems provide automated reasoning and knowledge-based solutions to assist in decision-making.

What is a rule-based expert system and how does it function?

• A rule-based expert system functions by randomly selecting options from a database.

• A rule-based expert system relies solely on user input without any predefined rules.

• A rule-based expert system uses predefined rules and a knowledge base to make decisions through an inference engine.

• A rule-based expert system uses machine learning algorithms to adapt its rules over time.

What role do expert systems play in financial services?

• Expert systems only provide customer support in financial services.

• Expert systems enhance decision-making, risk assessment, and automation in financial services.

• Expert systems replace human financial advisors entirely.

• Expert systems are primarily used for marketing strategies in finance.

How do knowledge bases contribute to the effectiveness of expert systems?

• Expert systems rely solely on user input without knowledge bases.

• Knowledge bases provide structured information and rules that enhance decision-making and problem-solving in expert systems.

• Knowledge bases are used for data storage but do not affect decision-making.

• Knowledge bases only store data without any rules.

What are the advantages of using expert systems in manufacturing?

• Higher labor costs

• Reduced production speed

• Increased dependency on manual processes

• The advantages of using expert systems in manufacturing include improved decision-making, increased efficiency, enhanced quality control, continuous operation, and knowledge retention.

In what ways can expert systems improve customer service in retail?

• Reducing the number of staff in stores

• Increasing the prices of products

• Limiting customer access to information

• Expert systems improve customer service by providing instant responses, personalizing experiences, automating tasks, and offering 24/7 support.

What challenges do expert systems face in the healthcare industry?

• Expert systems only assist in administrative tasks in healthcare.

• Expert systems are not used in healthcare.

• Challenges include data privacy concerns, integration with existing systems, and the need for continuous updates.

• Expert systems are always accurate and do not face challenges.

How can expert systems be utilized in supply chain management?

• Expert systems can only track shipments.

• They can optimize inventory levels, forecast demand, and enhance supplier selection.

• Expert systems are not applicable in supply chain management.

• They primarily focus on customer service in supply chains.

What is the significance of inference engines in expert systems?

• They function as user interfaces for expert systems.

• Inference engines only store data without processing it.

• They are responsible for processing information and applying rules to derive conclusions from the knowledge base.

• Inference engines are irrelevant to expert systems.