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INFSY540 Information Resources in Management

INFSY540 Information Resources in Management. Lesson 11 ECommerce. Finalizing Artificial Intelligence. Some AI Technologies. Expert Systems: Diagnose, respond & act like a human expert Neural Networks: Use data to predict outputs or interpret inputs

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INFSY540 Information Resources in Management

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  1. INFSY540Information Resources in Management Lesson 11 ECommerce

  2. Finalizing Artificial Intelligence

  3. Some AI Technologies • Expert Systems: Diagnose, respond & act like a human expert • Neural Networks: Use data to predict outputs or interpret inputs • Genetic Algorithms: Use data to find “optimal” solutions • Fuzzy Logic: Facilitate solutions to human vagueness problems • Robotics: Mimic physical human processes • Natural-Language Processing: Mimic human communication • Intelligent Tutorials: Facilitate human learning • Computer Vision: Mimic human sensory(visual) process • Virtual Reality: Mimic human reality inside a computer • Game Playing: Beat humans in games, e.g. chess

  4. Cognitive vs Biological AI • Cognitive-based Artificial Intelligence • Top Down approach • Attempts to model psychological processes • Concentrates on what the brain gets done • Biological-based Artificial Intelligence • Bottom Up approach • Attempts to model biological processes • Concentrates on how the brain works

  5. Cognitive AI Tools: Expert Systems Natural Language Fuzzy Logic Intelligent Agents Intelligent Tutorials Planning Systems Virtual Reality Biological AI Tools Neural Networks Speech Recognition Computer Vision Genetic Algorithms Evolutionary Programming Machine Learning Robotics Cognitive vs Biological AI

  6. Neural Networks vs Expert Systems • Neural Nets is to Expert Systems.... • As Recognition is to Thought Process • Some problems can use either one • How do the experts solve it? • Logical step-by-step fashion? … Expert System • Recognizing the big picture? … Neural Network • Is enough historical data present? • Yes. … Neural Network • No. … Expert System

  7. Neural Networks vs. Expert Systems • Can we use both together? YES! • Output of neural net used as a fact in expert system: • Vehicle suspension system diagnostics. • Neural net classifies the behavior pattern of the shock absorber (shock is worn, ok, etc.) • Expert system uses result to perform diagnosis of the whole system. • Expert System output as input to neural network: • Different expert systems can perform interpretation of individual events (ex. terrorist activities) • Interpretation can serve as input to neural network • Network identifies likelihood of perpetrator or commonalities among events

  8. Genetic Algorithms vs Neural Nets • Neural Networks: • Build models of the real world • Use models to make predictions • Genetic Algorithms: • Typically uses an existing model (Fitness Function) • Searches for a good (or optimal) solution to the model.

  9. Difference between Prediction and Optimization • Prediction: What is the nutrition content of a McDonald’s Happy Meal? • Optimization: What is the most nutritious meal at McDonald’s? • Solving optimization problems typically requires solving many iterations of smaller prediction problems.

  10. Genetic Algorithms withExpert Systems & Neural Nets • GA can use ES to test feasibility of a chromosome. • Constraints often easy to express in rules...... • GA can use trained NN as the Fitness Function. GA ES Is it feasible? NN How good is it? Fitness Value

  11. Genetic Algorithms withExpert Systems & Neural Nets If infeasible, return an extremely bad Fitness GA ES NN If it is a feasible solution, send to Neural Network Fitness Value

  12. Questions about Artificial Intelligence?

  13. ECommerceLearning Objectives • Identify advantages of e-commerce • Outline how e-commerce works • Identify challenges companies must overcome to succeed in e-commerce • Identify the major issues that threaten the continued growth of e-commerce

  14. Learning Objectives • List the key technology components that must be in place for successful e-commerce • Discuss key features of electronic payments systems needed for e-commerce • Identify some e-commerce applications • Outline key components of a successful e-commerce strategy

  15. An Introduction to Electronic Commerce

  16. Fig 8.1

  17. E-Commerce Challenges • Define strategy • Change distribution systems & work processes • Integrate web-based order processing with traditional systems

  18. Can you find examples of community, content & commerce on www.drugstore.com?

  19. Fig 8.3

  20. Fig 8.4

  21. Forms of E-Commerce • Business to Business (B2B) • Business to Consumer (B2C)

  22. E-Commerce Applications

  23. Retail and Wholesale • E-tailing: electronic retailing • Cybermalls • Wholesale e-commerce: B2B

  24. Fig 8.5

  25. Marketing • DoubleClick

  26. Table 8.1

  27. Table 8.2

  28. Priceline

  29. Technology Infrastructure

  30. Fig 8.6

  31. Web Server Hardware • Server platform • Hardware • Operating system • Website hosting • Capital investment • Technical staff • Must run 24-7-365 to avoid disrupting business & losing customers

  32. Web Server Software • Security & identification • Encryption • Retrieving & sending web pages • Web site tracking

  33. E-Commerce Software • Catalog management • Product configuration • Shopping cart • Transaction processing • Traffic data analysis

  34. Network Selection • Cost • Availability • Reliability • Security • Redundancy

  35. Electronic Payment Systems

  36. Payment Security • Authentication • Digital certificate • Certificate authority (CA) • Encryption • Secure Sockets Layer (SSL)

  37. Payment Mechanisms • Electronic cash • Identified electronic cash • Anonymous electronic cash (digital cash) • Electronic wallets • Smart, credit,charge & debit cards

  38. Threats to E-Commerce

  39. Threats to E-Commerce Security

  40. Threats to E-Commerce • Intellectual property • Fraud • On-line auctions • Spam • Pyramid schemes • Investment fraud • Stock scams

  41. Threats to E-Commerce • Privacy • Online profiling • Clickstream data

  42. Fig 8.8 TRUSTe Seal

  43. Fig 8.9 BBB Online Privacy Seal

  44. Table 8.3 How to Protect Your Privacy While On-Line

  45. Strategies for Successful E-Commerce

  46. Developing an Effective Web Presence • Obtain information • Learn about products or services • Buy products or services • Check order status • Provide feedback or complaints

  47. Putting Up a Web Site • In-house development • Web site hosting companies • Storefront brokers

  48. Driving Traffic to Your Web Site • Domain names • Meta tags • Traffic logs

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