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THE WALLACE E. CARROLL SCHOOL OF MANAGEMENT MD254: e-Service Operations Management Spring 2003 |
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Week 9 e-Service Process Technology: Analyzing Web Site Usage – Recommender Systems Assigned Readings “Recommender Systems,” P. Resnick, and H.R. Varian, Communications of the ACM, March 1997, (http://www.acm.org/cacm/MAR97/resnick.html). “Automatic Personalization Based on Web Usage Mining,” B. Mobasher, R. Cooley, and J. Srivastava, Communications of the ACM, Vol. 43, No. 8, August 2000, p. 142-151 (http://maya.cs.depaul.edu/~classes/ect584/papers/mobasher.pdf). CASE STUDY: “Amazon.com Recommendations: Item-to-Item Collaborative Filtering,” IEEE Internet Computing, January/February 2003. (Download Here) This article is a report of Amazon.com’s recommendation systems, and a comparison to other possible recommendation systems. CASE QUESTIONS: 1. What advantages and disadvantages does the collaborative filtering method used in Amazon’s recommender have, relative to the other possible methods? 2. In what way(s) does a product recommendation system such as Amazon’s need to be scalable? NOTE: If you are interested in learning more about data mining, and website mining in specific, you may want to visit Dr. Bamshad Mobasher’s web site at DePaul University, for his course on Web Data Mining (http://maya.cs.depaul.edu/~classes/ect584/lecture.html) and his page of resources (http://maya.cs.depaul.edu/~classes/ect584/resource.html).
Related Readings: For Further Information
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