Preliminaries -- Preface -- Contents -- Introduction -- 1. Introduction -- 2. Computational Intelligence and Computational Web Intelligence -- 3. Hybrid Intelligence and Hybrid Web Intelligence -- 4. Conclusions -- Bibliography -- Chapter 1. Recommender Systems Based on Representations -- 1.1 Introduction -- 1.2 Recommender Systems -- 1.3 The Representation Schema -- 1.4 Intentionally Expressed Preferences -- 1.5 User Profiles -- 1.6 Using Experience for Justification -- 1.7 Conclusion -- Bibliography -- Chapter 2. Web Intelligence: Concept-Based Web Search -- 2.1 Introduction -- 2.2 Fuzzy Conceptual Model and Search Engine -- 2.3 Construction of RBF network -- 2.4 Generation of CFSs -- 2.5 Illustrative Example of CFSs -- 2.6 Previous Applications of CFSs -- 2.6.1 Information Retrieval System -- 2.6.2 Exposure of Illegal Web Sites Using : Conceptual Fuzzy Sets-Based Information Filtering System -- 2.6.2.1 System Description -- 2.6.2.2 CFSs Unit -- 2.6.2.3 Evaluations Procedure -- 2.6.2.4 Results -- 2.6.2.5 Fuzzy-TF.IDF -- 2.6.3 Conceptual Fuzzy Sets-Based Navigation System for Yahoo! -- 2.6.3.1 Navigation System for Yahoo! -- 2.6.3.2 Navigation System -- 2.6.3.3 Path base -- 2.6.3.4 Experiments -- 2.6.3.5 Determine the repeat number of propagation -- 2.6.3.6 Search the paths -- 2.6.3.7 3D user inteface -- 2.7 Concept-Based Web Communities for GoogleTM Search Engine -- 2.7.1 System Architecture -- 2.7.2 CFSs Unit -- 2.7.3 SVM Unit -- 2.7.4 Classifier Unit -- 2.7.4.1 Make Vector Unit -- 2.7.4.2 CFSs Unit -- 2.7.4.3 SOM Unit -- 2.7.5 Experiment and Result -- 2.8 Challenges and Road Ahead -- 2.9 Conclusions -- Acknowledgement -- Bibliography -- Chapter 3. A Fuzzy Logic Approach to Answer Retrieval from the World-Wide-Web -- 3.1 Introduction -- 3.2 Multi-Disciplinary Approach -- 3.3 Practical Constraints -- 3.4 The Ladder Approach.

3.5 Handling the Bottom Layer: Indexing/Categorization -- 3.6 Middle Layer Solutions: Answer Retrieval -- 3.6.1 Fuzzy Sequence Concept -- 3.6.2 Sentence Scoring -- 3.6.3 Paragraph Scoring -- 3.6.4 Enhancements to Fuzzy Sequence Approach -- 3.7 Top Layer Solutions: Answer Formation -- 3.8 Model Validation -- 3.9 Conclusions -- Bibliography -- Chapter 4. Fuzzy Inference Based Server Selection in Content Distribution Networks -- 4.1 Introduction -- 4.2 Server Selection in Content Distribution Networks -- 4.2.1 A Server Selection Model -- 4.2.2 Server Selection Criteria -- 4.2.3 Related Work -- 4.3 Fuzzy Inference Based Server Selection Scheme -- 4.4 Performance Evaluation -- 4.4.1 Simulation Topology and Parameters -- 4.4.2 Simulated Fuzzy System -- 4.4.3 Performance Comparison -- 4.4.3.1 Even Request Pattern -- 4.4.3.2 Uneven Request Pattern -- 4.4.3.3 Measurement Overhead Comparison -- 4.5 Conclusions and Future Work -- Acknowledgement -- Bibliography -- Chapter 5. Recommendation Based on Personal Preference -- 5.1 Introduction -- 5.2 The Existing Techniques -- 5.3 The New Approach -- 5.4 Discussion -- Bibliography -- Chapter 6. Fuzzy Clustering and Intelligent Search for a Web-Based Fabric Database -- 6.1 Introduction -- 6.2 The On-line Database and Search Engine -- 6.3 Fuzzy Linear Clustering -- 6.4 Experiments on Fuzzy Clustering -- 6.5 Conclusions and Future Work -- Acknowledgement -- Bibliography -- Chapter 7. Web Usage Mining: Comparison of Conventional, Fuzzy and Rough Set Clustering -- 7.1 Introduction -- 7.2 Literature Review -- 7.2.1 Review of K-Means -- 7.2.2 Modified K-Means based on Rough Set Theory -- 7.2.3 Fuzzy C-means Clustering -- 7.3 Study Data and Design of the Experiment -- 7.3.1 Data Description -- 7.3.2 Data Preparation -- 7.4 Results and Discussion -- 7.5 Summary and Conclusions -- Bibliography.

Chapter 8. Towards Web Search using Contextual Probabilistic Independencies -- 8.1 Introduction -- 8.2 Bayesian Networks -- 8.3 Context Specific Independence -- 8.4 Contextual Weak Independence -- 8.4.1 The Weak-Join Operator -- 8.4.2 The CWI Inference Process -- 8.5 Conclusions -- Bibliography -- Chapter 9. Neural Expert System for Vehicle Fault Diagnosis via The WWW -- 9.1 Introduction -- 9.2 Intelligent Data Mining for Vehicle Fault Diagnosis -- 9.2.1 Case-based reasoning -- 9.2.2 Rule-based reasoning -- 9.2.3 Neural networks -- 9.2.4 Combined CBR-RBR_NN data mining process -- 9.3 Vehicle Service Database -- 9.4 Knowledge Base Construction -- 9.4.1 Neural network model generation -- 9.4.2 Rule base generation -- 9.5 Online Vehicle Fault Diagnosis -- 9.5.1 The user's experience -- 9.6 Experiments -- 9.6.1 Comparison with tradition kNN -- 9.7 Conclusion -- Bibliography -- Chapter 10. Dynamic Documents in the Wired World -- 10.1 Introduction -- 10.2 Background and Related Work on Dynamic Document Creation -- 10.2.1 Variable Information Documents -- 10.2.2 Scripts, Dynamic HTML, and Active Server Pages -- 10.2.3 Style Sheets and Transformational Languages -- 10.2.4 Personalized Information Services -- 10.2.5 Constraint-Based Research -- 10.3 Dynamic Document Assembly as a Multiobjective Constrained Optimization Problem -- 10.3.1 Initial Constraint Satisfaction Based Approach -- 10.3.2 Genetic Algorithm Based Constrained Multiobjective Optimization Approach -- 10.3.2.1 Document Parameters as Genes -- 10.3.2.2 Design Qualities as Objectives -- 10.3.2.3 Optimizing Design Qualities -- 10.3.3 Benefits of the Multiobjective Optimization Approach -- 10.3.3.1 Easier Document Specification -- 10.3.3.2 Enabling More Dynamic Document Instances -- 10.3.4 New Workflows Enabled by the Approach -- 10.3.4.1 Prepress Workflow Issues -- 10.3 4.2 New Workflow Example.

10.4 Future Work -- 10.5 Summary -- Bibliography -- Chapter 11. Proximity-Based Supervision for Flexible Web Page Categorization -- 11.1 Introduction -- 11.2 P-FCM algorithm -- 11.2.1 Problem formulation and underlying notation -- 11.3 Some Illustrative Examples -- 11.4 Benchmark -- 11.5 Related Works -- 11.6 Conclusion -- 11.7 Acknowledgments -- Bibliography -- Chapter 12. Web Usage Mining: Business Intelligence from Web Logs -- 12.1 Introduction -- 12.2. Mining Framework Using Hybrid Computational Intelligence Paradigms (CI) -- 12.2.1 Clustering Algorithms for Segregating Similar Visitors -- Fuzzy Clustering Algorithm -- Self Organizing Map (SOM) -- 12.2.2 Computational Intelligence (CI) for Analysis of Visitor Trends -- Artificial Neural Network (ANN) -- Linear Genetic Programming (LGP) -- Fuzzy Inference Systems (FIS) -- Optimization of Fuzzy Clustering Algorithm -- Optimization of Fuzzy Inference System -- 12.2.3 Mining Framework Using Intelligent Miner (i-Miner) -- Chromosome Modeling and Representation -- 12.3 Experimental Setup-Training and Performance Evaluation -- 12.4 Conclusions -- Acknowledgements -- Bibliography -- Chapter 13. Intelligent Content-Based Audio Classification and Retrieval for Web Application -- 13.1 Introduction -- 13.2 Spoken Document Retrieval and Indexing -- 13.3 Music Information Retrieval, Indexing and Content Understanding -- 13.4 Content-Based Audio Classification and Indexing -- 13.4.1 The Audio Databases -- 13.4.2 Audio Feature Extraction, Normalization and Selection -- 13.4.3 Audio Classification Experimental Results -- 13.5 Content-Based Audio Retrieval -- 13.5.1 Performance Measurement -- 13.5.2 Audio Retrieval Experimental Results -- 13.5.3 Content-based Audio Retrieval With Relevance Feedback -- 13.5.3.1 Proposed Relevance Feedback Algorithm -- 13.5.3.2 Query Refining and Other Issues.

13.5.3.3 Experimental Results -- 13.6 Audio Retrieval Based on the Concepts of Audio Ontology and Audio Item -- 13.6.1 Ontology and Audio Ontology -- 13.6.2 MPEG-21 and Audio Item -- 13.6.3 Audio Retrieval using Audio Item with Ontology -- 13.7 Conclusions and Outlook -- Bibliography -- Chapter 14. Developing an Intelligent Multi-Regional Chinese Medical Portal -- 14.1 Introduction -- 14.2 Related Work -- 14.2.1 Internet Searching and Browsing -- 14.2.2 Domain-specific Search Engines -- 14.2.3 Searching Support Techniques -- 14.2.3.1 Meta-search -- 14.2.4 Browsing Support Techniques -- 14.2.4.1 Categorization-Document Overview -- 14.2.4.2 Summarization-Document Preview -- 14.2.5 Regional Difference among Chinese Users -- 14.2.6 Current Search Engines and Medical Portals in Three Regions -- 14.2.7 Summary -- 14.3 Research Prototype - CMedPort -- 14.3.1 Content Creation -- 14.3.2 Meta-search Engines -- 14.3.3 Encoding Converter -- 14.3.4 Chinese Summarizer -- 14.3.5 Categorizer -- 14.3.6 User Interface -- 14.4 Pilot Study -- 14.5 Future Directions -- Acknowledgement -- Bibliography -- Chapter 15. Multiplicative Adaptive User Preference Retrieval and its Applications to Web Search -- 15.1 Introduction -- 15.2 Vector Space and User Preference -- 15.3 Multiplicative Adaptive Query Expansion Algorithm -- 15.4 Multiplicative Gradient Descent Search Algorithm -- 15.5 Meta-Search Engine MARS -- 15.6 Meta-Search Engine MAGrads -- 15.7 Concluding Remarks -- Bibliography -- Chapter 16. Scalable Learning Method to Extract Biological Information from Huge Online Biomedical Literature -- 16.1 Introduction -- 16.2 Related Work -- 16.3 Text Mining with Information Extraction for Biomedical Literature Mining -- 16.3.1 Select Potential promising Biomedical Articles from the Biomedical Literature Databases.

16.3.2 Protein Tagging and Extraction of Sentences of Interests.