Advances in Web Mining and Web Usage Analysis

1. Front Matter

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2. Adaptive Website Design Using Caching Algorithms

   • Justin Brickell, Inderjit S. Dhillon, Dharmendra S. Modha

   Pages 1-20

3. Incorporating Usage Information into Average-Clicks Algorithm

   • Kalyan Beemanapalli, Ramya Rangarajan, Jaideep Srivastava

   Pages 21-35

4. Nearest-Biclusters Collaborative Filtering with Constant Values

   • Panagiotis Symeonidis, Alexandros Nanopoulos, Apostolos Papadopoulos, Yannis Manolopoulos

   Pages 36-55

5. Fast Categorization of Web Documents Represented by Graphs

   • Alex Markov, Mark Last, Abraham Kandel

   Pages 56-71

6. Leveraging Structural Knowledge for Hierarchically-Informed Keyword Weight Propagation in the Web

   • Jong Wook Kim, K. Selçuk Candan

   Pages 72-91

7. How to Define Searching Sessions on Web Search Engines

   • Bernard J. Jansen, Amanda Spink, Vinish Kathuria

   Pages 92-109

8. Incorporating Concept Hierarchies into Usage Mining Based Recommendations

   • Amit Bose, Kalyan Beemanapalli, Jaideep Srivastava, Sigal Sahar

   Pages 110-126

9. A Random-Walk Based Scoring Algorithm Applied to Recommender Engines

   • Augusto Pucci, Marco Gori, Marco Maggini

   Pages 127-146

10. Towards a Scalable kNN CF Algorithm: Exploring Effective Applications of Clustering

    • Al Mamunur Rashid, Shyong K. Lam, Adam LaPitz, George Karypis, John Riedl

    Pages 147-166

11. Detecting Profile Injection Attacks in Collaborative Filtering: A Classification-Based Approach

    • Chad A. Williams, Bamshad Mobasher, Robin Burke, Runa Bhaumik

    Pages 167-186

12. Predicting the Political Sentiment of Web Log Posts Using Supervised Machine Learning Techniques Coupled with Feature Selection

    • Kathleen T. Durant, Michael D. Smith

    Pages 187-206

13. Analysis of Web Search Engine Query Session and Clicked Documents

    • David Nettleton, Liliana Calderón-Benavides, Ricardo Baeza-Yates

    Pages 207-226

14. Understanding Content Reuse on the Web: Static and Dynamic Analyses

    • Ricardo Baeza-Yates, Álvaro Pereira, Nivio Ziviani

    Pages 227-246

15. Back Matter

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This book contains the postworkshop proceedings with selected revised papers from the 8th international workshop on knowledge discovery from the Web, WEBKDD 2006. The WEBKDD workshop series has taken place as part of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) since 1999. The discipline of data mining delivers methodologies and tools for the an- ysis of large data volumes and the extraction of comprehensible and non-trivial insights from them. Web mining, a much younger discipline, concentrates on the analysisofdata pertinentto the Web.Web mining methods areappliedonusage data and Web site content; they strive to improve our understanding of how the Web is used, to enhance usability and to promote mutual satisfaction between e-business venues and their potential customers. Inthelastfewyears,theinterestfortheWebasamediumforcommunication, interaction and business has led to new challenges and to intensive, dedicated research.Many ofthe infancy problems in Web mining have been solvedby now, but the tremendous potential for new and improved uses, as well as misuses, of the Web are leading to new challenges. ThethemeoftheWebKDD2006workshopwas“KnowledgeDiscoveryonthe Web”, encompassing lessons learned over the past few years and new challenges for the years to come. While some of the infancy problems of Web analysis have beensolvedandproposedmethodologieshavereachedmaturity,therealityposes newchallenges:TheWebisevolvingconstantly;siteschangeanduserpreferences drift. And, most of all, a Web site is more than a see-and-click medium; it is a venue where a user interacts with a site owner or with other users, where group behavior is exhibited, communities are formed and experiences are shared.

• DOM
• Session
• algorithms
• association rule mining
• classification
• clustering
• data mining
• filtering
• graph mining
• learning
• machine learning
• pattern mining
• recommender systems
• security
• user profiling

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