2. Use of Agents in ECommerce Product Search/Identification (eg “Eyes” by amazon) Information Brokering Automated Negotiation Web Marketing

3. Proposed Area of Interest: Product Recommendation Adopted by websites like Amazon Netflix Walmart Agent should be aware of Interests Preferences Liking Predict future Needs

4. Traditional Methods Adopted Implicit Engines Explicit Engines Content Based method Collaborative Method Hybrid method

5. Related Work Yunhong XU, Jian Ma, “USING SOCIAL NETWORK ANALYSIS AS A STRATEGY FOR E- COMMERCE RECOMMENDATION”, 2009 Bin Xiao, Esma A,, Josef Manuel Fernandez, "PCFinder:An Intelligent Product Recommendation Agent for E-Commerce,"2003 IEEE International Conference on E-Commerce Sangkil Moon, Gary J. Russell, “A SPATIAL CHOICE MODEL FOR PRODUCT RECOMMENDATIONS”, 2003

6. Proposed Approach Build a Recommendation System: Context Aware Agents embedded in mobile device Agents Deployed to monitor social Network Behavior of User

7. Context Based Agent Doctor Student Businessman

8. Agents Monitoring Behavior of User on Social Networks Facebook page

9. Evaluation Criteria Experiment with well defined set of users profile like Graduate students etc. Get feedback on quality of recommendation obtained. Extend to include users with different profile.

10. Conclusion Use of Intelligent agents in different aspects of eCommerce Traditional methods adopted in Product Recommendation System. New proposed approaches for Product Recommendation exploiting : User’s context aware data Behavior on web.