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Lectures & Course Material

Date
Topics & Reading
Mar 31 Overview Web Data Mining and E-Business Analytics
Reading:
  • Chapters 1 and 2 of Berry and Linoff
  • Data Mining on the Web - short article by Dan R. Greening, written for webtechniques.com.
  • (Online Paper # 1) Web Mining: Information and Pattern Discovery on the World Wide Web, by Robert Cooley, Bamshad Mobasher, and Jaideep Srivastava, ICTAI 1997.

    Watch this Interview:
  • This is an interview with Prof. Bamshad Mobasher of DePaul University in a recent episode of "Politics in Perspective" program on the cable Channel 19 which airs in the Chicago area. The topic is "Data Mining, security, and Privacy". You can view the full program (approx. 30 minutes) in Windows Media. Note: you will need Internet Explorer to be able to view the program.
    		•
    Apr 07 Knowledge Discovery Process; Data Preparation for Mining
    Reading:
  • Chapters 3 and 17 of Berry and Linoff
  • Data Mining Overview
  • (Online Paper # 9) Driving e-Commerce Profitability From Online and Offline Data, White paper form Torrent Systems.
  • (Online Paper # 3) Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data, by Jaideep Srivastava, et. al., SIGKDD Explorations, January 2000.
    • Apr 14 Data Mining Techniques: Mining Association Rules and Sequential Patterns
    Reading:
  • Chapter 2 of B. Liu's Book
  • Chapter 9 of Berry and Linoff
  • (Online Paper # 5) Web Usage Mining for Web Site Evaluation, by Myra Spiliopoulou, Communications of ACM, August 2000.
  • (Online paper # 7) An Internet-enabled Knowledge Discovery Process, by Alex Buchner, et. al., MINEit Software Ltd., 1999.
    • Apr 21 Data Mining Techniques: Classification & Prediction
    Reading:
  • Chapter 3 of B. Liu's Book
  • Chapter 6 of Berry and Linoff
  • (Online paper # 33) Modeling Web Robot Navigation Patterns, by Pang-Ning Tan and Vipin Kumar, WebKDD Workshop at the ACM SIGKDD Conference, 2000.
  • Note: An additional description of the ID3 and C4.5 algorithms can be found in the document "Building Classification Models: ID3 and C4.5" from the AI course at Temple university.
    • Apr 28 Data Mining Techniques: Clustering; Memory-Based Reasoning
    Reading:
  • Chapter 4 of B. Liu's Book
  • Chapters 11 and 8 of Berry and Linoff
  • (Online Paper # 22) Text-Learning and Related Intelligent Agents: A Survey, by Dunja Mladenic, IEEE Intelligent Systems, July/August 1999.
  • (Online Paper # 13) Clustering Users of Large Web Sites into Communities, by Georgios Paliouras, et. al., ICML 2000.
    • May 05 Web Usage Mining: Data Preparation and Integration
    Reading:
  • Chapter 12 of B. Liu's Book
  • (Online Paper # 4) Data Preparation for Mining World Wide Web Browsing Patterns, by Robert Cooley, Bamshad Mobasher, and Jaideep Srivastava, Knowledge and Information Systems, Volume 1, No. 1, 1999.
  • (Online paper # 32) Lessons and Challenges from Mining Retail E-Commerce Data, by Ron Kohavi, et al., Journal of Machine Learning, 2003.
    • May 12 Web Usage Mining: E-Metrics and E-Commerce Data Analysis, Predictive  Web Analytics
    Reading:
  • Chapters 14 and 4 of Berry and Linoff
  • (Online paper #10) E-Commerce Intelligence: Measuring, Analyzing, and Reporting on Merchandising Effectiveness of Online Stores, by Stephen Gomory, et. al., IBM T. J. Watson Research Center.
  • (Online paper #11) E-Metrics Business Metrics For The New Economy, White Paper from NetGenesis.
    • May 19 Web Personalization and Recommender Systems
    Reading:
  • (Online paper # 14) Automatic Personalization Based on Web Usage Mining, by Bamshad Mobasher, Robert Cooley, and Jaideep Srivastava, Communications of ACM, August 2000.
  • (Online paper # 28) Analysis of Recommendation Algorithms for E-Commerce, by Badrul Sarwar, et. al., ACM Electronic Commerce Conference, November 2000.
  • (Online paper # 15) Integrating Web Usage and Content Mining for More Effective Personalization, by Bamshad Mobasher et. al., EC-Web 2000.
    • May 26 No Class- Memorial Day
    Reading:
  • (Online Paper # 20) Text Mining: Finding Nuggets in Mountains of Textual Data, by Jochen Dorre, Peter Gerstl, and Roland Seiffert, KDD 1999.
  • (Online Paper # 19) Data mining for hypertext: A tutorial survey, by Soumen Chakrabarti, SIGKDD Explorations, January 2000.
  • (Online Paper # 25) Extracting Patterns and Relations from the World Wide Web, by Sergey Brin, Stanford University.
    • Jun 02 Web Content Mining, Link Mining & Social Network Analysis
    Final Projects Due - Sunday, June 8, 11:59 PM


    Copyright © 2007-2008, Bamshad Mobasher, School of CTI, DePaul University.