1. HOMMER: Holistic Model for Minority Education & Research Intelligent E-Commerce Systems Department of Computer and Information Sciences by Bhanu Prasad May 5th, 2004

2. Outline 1. What is E-Commerce? 2. Problems addressed in B2C E-Commerce 3. References Department of Computer and Information SciencesMay 5th, 2004

3. E-Commerce E-commerce is the use of computing and communication technologies in commerce between a business and its customers. The expected market share of e-commerce is around 9 Billion Dollars by 2005 (according to Dataquest) Two types: B2C and B2B Department of Computer and Information SciencesMay 5th, 2004

4. AI in B2C E-Commerce Product selection and recommendation Online negotiation Automated online shopping Online auctions Department of Computer and Information SciencesMay 5th, 2004

5. Online Product Selection and Recommendation Decision support approaches (based on weight- vectors) Other Knowledge-Based Approaches Department of Computer and Information SciencesMay 5th, 2004

6. Weight Vector-Based Approaches for product retrieval and recommendation If the system recommends a list of prioritized products and the user does not select the topmost one then there is a provision for the system to learn Users with similar preferences are categorized into groups Weights represent mean preferences of the groups [3] Department of Computer and Information SciencesMay 5th, 2004

7. Knowledge-Based Approaches for Product Retrieval, Recommendation, and Negotiation Case-Based Reasoning Approaches [1], [4], [5] –Usage of Previous knowledge in solving the current problem Agent-Based Approaches [6] –Active Agents –Passive Agents –Hybrid Agents Department of Computer and Information SciencesMay 5th, 2004

8. Domain Independent E- commerce System Most of the e-commerce systems are tailored for specific products. We are working on a Domain Independent e- commerce system. Knowledge Hierarchies, Inference mechanisms, and different kinds of negotiation approaches are used for this purpose [2] Department of Computer and Information SciencesMay 5th, 2004

9. Automated online shopping Development of a system that relieves a lot of burden off the user by automating the process of searching, negotiating and buying the product on behalf of the users Based on Intelligent agents and technologies such as XML, SOAP, WSDL and UDDI Department of Computer and Information SciencesMay 5th, 2004

10. References 1.Bhanu Prasad: Intelligent E-Commerce, Journal of E-Commerce Research. Volume 4, No 2, 2003. 2.Bhanu Prasad: A Domain Independent E- Commerce System for Product Recommendation in B2C E-Commerce. Proceedings of 3rd International Interdisciplinary Conference on Electronic Commerce, 2003. Pages 129-134. 3.Bhanu Prasad: Weight Vector-Based Approach for Product Recommendation in E-Commerce. Lecture Notes in Artificial Intelligence, Springer LNCS 2412, 2002. pages 200-205. Department of Computer and Information SciencesMay 5th, 2004

11. References 4. Bhanu Prasad and Clementi Joao: A Knowledge-based E-Commerce System for Product Recommendation in Sports Domain. Proceedings of the International Conference on Information and Knowledge Engineering (IKE’02), Las Vegas, Nevada, USA, 2002. pages 46-51 5. Bhanu Prasad: Knowledge-Based E-Commerce. Proceedings of the 2nd International Interdisciplinary Conference on Electronic Commerce, Poland, 2002. pages 98-105 Department of Computer and Information SciencesMay 5th, 2004

12. References 6. An Agent-Based Negotiation System for B2C E- Commerce. Accepted for the International Conference on Information and Knowledge Engineering (IKE), to be held in Las Vegas, NV during June, 2004. Department of Computer and Information SciencesMay 5th, 2004