| Title Page | 1 |
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| Preface | 5 |
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| Contents | 6 |
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| Part I Invited Lectures | 9 |
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| Fuzzy Ontologies and Fuzzy Markup Language: A Novel Vision inWeb Intelligence | 10 |
| Introduction | 10 |
| Fuzzy Ontologies and Fuzzy Markup Language | 11 |
| Fuzzy Ontologies | 11 |
| Fuzzy Markup Language | 12 |
| Fuzzy Ontologies and FML: Real-World Applications | 13 |
| Conclusion and Future Works | 16 |
| References | 16 |
| Loose Ontological Coupling and the Social Semantic Web | 18 |
| Introduction | 18 |
| Loosely-Coupled Ontologies | 19 |
| Emergent Semantics | 20 |
| Conclusions | 21 |
| References | 21 |
| Part II Regular Papers | 23 |
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| Further Experiments in Sentiment Analysis of French Movie Reviews | 24 |
| Introduction | 24 |
| Previous Work | 25 |
| FeatureDesign | 26 |
| Lexical Features | 26 |
| Morpho-syntactic Features | 26 |
| Semantic Features | 27 |
| Experiments | 28 |
| Results and Discussion | 28 |
| Conclusions | 32 |
| References | 32 |
| Querying over Heterogeneous and Distributed Data Sources | 34 |
| Introduction | 34 |
| Related Works | 35 |
| Virtual-Q System | 37 |
| Virtual Query Engine Architecture | 38 |
| Query Process | 39 |
| Prototype | 41 |
| Conclusion and Future Work | 42 |
| References | 43 |
| Experiments in Bayesian Recommendation | 44 |
| Introduction | 44 |
| Related Work | 45 |
| Notation | 45 |
| Bayesian Recommendation | 45 |
| Multinomial Model | 46 |
| Dirichlet Prior | 46 |
| Gaussian Model | 47 |
| Experiments | 49 |
| Evaluation Metrics | 49 |
| Results | 49 |
| Sparsity | 50 |
| Conclusions | 52 |
| Future Work | 52 |
| References | 52 |
| Experiences of Knowledge Visualization in Semantic Web Applications | 54 |
| Introduction | 54 |
| Knowledge Visualization in the Semantic Web Context | 55 |
| EasyOnto | 56 |
| Integrated Environments for Knowledge Management and Visualization | 58 |
| IRCS Framework | 59 |
| The AWI Environment | 61 |
| Conclusions | 63 |
| References | 63 |
| Tagsonomy : Easy Access to Web Sites through a Combination of Taxonomy and Folksonomy | 65 |
| Introduction | 66 |
| Web Access through Taxonomies and Folksonomies | 66 |
| Combining the Taxonomy and Folksonomy Approaches | 67 |
| The Easy Access (EA) Project | 68 |
| Test Case: Applying the EA Tagsonomy to a Web Site | 70 |
| Preliminary Evaluation | 72 |
| Conclusions | 73 |
| References | 74 |
| Conceptual Query Expansion and Visual Search Results Exploration forWeb Image Retrieval | 76 |
| Introduction | 76 |
| Related Work | 78 |
| Conceptual Query Expansion for Image Search | 79 |
| Extracting Concepts from Wikipedia | 79 |
| Ranking the Extracted Concepts | 80 |
| Generating Expanded Queries | 81 |
| Visual and Conceptual Search Results Exploration | 81 |
| Multi-resolution SOM-Based Image Organization | 82 |
| Concept Hierarchy Focusing and Filtering | 82 |
| Conclusions and Future Work | 84 |
| References | 84 |
| Memoria-Mea: Combining Semantic Technologies and Interactive Visualization Techniques for Personal Information Management | 86 |
| Introduction | 86 |
| Related Work | 87 |
| Memoria-Mea: Logical Architecture | 88 |
| Memoria-Mea: Technical Architecture | 88 |
| Prototype | 90 |
| Visualization Module: MemoSIV | 91 |
| Annotation Module: MemoSAM | 92 |
| Conclusion and Future Works | 94 |
| References | 94 |
| Cylindric Extensions of Fuzzy Sets. An Application to Linguistic Summarization of Data | 96 |
| Introduction | 96 |
| The Definitions of Fuzzy Sets and Their Cylindric Extensions | 97 |
| Linguistic Summaries of Databases | 97 |
| Compound Linguistic Expressions Represented by Cylindric Extensions of Fuzzy Sets | 98 |
| Summaries with Compound Summarizers | 99 |
| Summaries with Qualifiers | 100 |
| Quality Measures | 100 |
| Defining Degree of Covering via Cylindric Extensions | 101 |
| Defining Degree of Appropriateness Using Cylindric Extensions | 102 |
| Conclusions | 102 |
| References | 103 |
| Comparison of Selected Methods for Document Clustering | 104 |
| Introduction | 104 |
| Applied Methods of Cluster Analysis | 105 |
| Similarity Measure | 106 |
| Clustering Criterion Functions | 106 |
| Clustering Methods | 106 |
| Quality Measures | 108 |
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