WEBKDD 2000 Papers

Worskhop on Web Mining for E-Commerce -- Challenges and Opportunities

Sunday, August 20, 2000, Boston, MA, USA


Session I: Web Personalization and Recommender Systems

  • Discovery of Aggregate Usage Profiles for Web Personalization (PDF)

  • Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa, Yuqing Sun, Jim Wiltshire
  • A Regression-Based Approach for Scaling-Up Personalized Recommender Systems in E-Commerce (Postscript, PDF),

  • Slobodan Vucetic and Zoran Obradovic
  • Application of Dimensionality Reduction in Recommender System - A Case vStudy (PDF),

  • Badrul M. Sarwar, George Karypis, Joseph A. Konstan, John T. Riedl  
  • Collaborative Recommendation via Adaptive Association Rule Mining (Postscript, PDF),

  • Weiyang Lin, Sergio A. Alvarez, Carolina Ruiz  
  • A Synthesized Learning Approach for Web-Based CRM (PDF),

  • Wei-Lun Chang, Soe-Tsyr Yuan

    Session II: Mining Frameworks and Case-Studies

  • Integrating E-Commerce and Data Mining: Architecture and Challenges (Postscript, PDF),

  • Suhail Ansari, Ron Kohavi, Llew Mason, and Zijian Zheng  
  • Analyzing the footsteps of your customers, A case study by ASK|net and SAS Institute GmbH (Postscript, PDF),

  • Christiane Theusinger, Klaus-Peter Huber  
  • The Marriage of Market Basket Analysis to Predictive Modeling: The Essential Challenge in Exploiting Web-Log Files for Prediction (PDF),

  • Sanford Gayle  
  • A Framework for Self Adaptive Websites: Tactical versus Strategic Changes (PDF),

  • Filip Coenen, Gilbert Swinnen, Koen Vanhoof, Geert Wets

    Session III: Navigation Analysis

  • Web usage mining, site semantics, and the support of navigation (Postscript, PDF)

  • Bettina Berendt  
  • Navigation Analysis Tool based on the Correlation between Contents Distribution and Access Patterns (PDF)

  • Hiroki Kato, Takehiro Nakayama, Yohei Yamane  
  • Mining web navigation path fragments (Postscript, PDF),

  • Wolfgang Gaul, Lars Schmidt-Thieme  
  • Modeling of Web Robot Navigational Patterns (Postscript, PDF)

  • Pang-Ning Tan, Vipin Kumar