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Dynamic Linking of Web Resources: Customisation and Personalisation | p. 1 |
Introduction | p. 1 |
COHSE | p. 5 |
Deploying COHSE | p. 6 |
Portals | p. 8 |
Architecture | p. 9 |
COHSE Portlet | p. 12 |
Personalisation | p. 14 |
User Tasks on the Web | p. 17 |
Related Work | p. 20 |
Summary and Discussion | p. 21 |
References | p. 22 |
A Multi-Purpose Ontology-Based Approach for Personalised Content Filtering and Retrieval | p. 25 |
Introduction | p. 25 |
Ontology-Based Personalisation for Content Retrieval | p. 27 |
Adaptation of Semantic User Preferences | p. 30 |
Automatic Creation and Update of Semantic Preferences | p. 31 |
Eploitation of Semantic Links Between Concepts for Preferences Learning | p. 33 |
Contextual Personalisation | p. 36 |
Context Representation | p. 36 |
Evaluation of Personalisation in Context | p. 37 |
Augmented Social Networking and Collaborative Filtering | p. 40 |
Semantic Group Profiling | p. 40 |
Semantic Social Networking | p. 43 |
Semantic Profile Expansion for Collaborative Group Profiling | p. 46 |
Conclusions | p. 48 |
References | p. 49 |
Analysing the Behaviour of Students in Learning Management Systems with Respect to Learning Styles | p. 53 |
Introduction | p. 53 |
Felder-Silverman Learning Style Model | p. 55 |
Investigated Patterns of Behaviour | p. 56 |
Design of the Study | p. 57 |
Description of the Course | p. 57 |
Instrument for Identifying Learning Styles | p. 58 |
Extensions in Moodle for Tracking Students' Behaviour | p. 58 |
Results | p. 59 |
Behaviour Vs. Learning Style Preferences | p. 60 |
Correlations Between Behaviour and Learning Style Preferences | p. 65 |
Benefits | p. 68 |
Related Work | p. 70 |
Conclusion and Future Work | p. 71 |
References | p. 72 |
Improving Image Retrieval Using Semantic Resources | p. 75 |
Introduction | p. 75 |
Related Work | p. 77 |
Ontological Issues | p. 79 |
Hierarchies | p. 79 |
Picturable Objects | p. 80 |
Automatic Ontology Building | p. 81 |
Visual Ontology Construction | p. 82 |
The WordNet Nouns Hierarchy | p. 82 |
Image Database Constitution | p. 83 |
Image Retrieval Phase | p. 84 |
Image Clustering | p. 88 |
Limits | p. 90 |
Image Processing Limitations | p. 90 |
WordNet Coverage | p. 90 |
Complex Queries | p. 91 |
Quality of the Semantic Structure | p. 91 |
Evaluation | p. 92 |
Experimental Settings | p. 92 |
Results | p. 92 |
Perspectives | p. 93 |
Conclusions | p. 94 |
References | p. 95 |
Implementing an Internet Image Search Service Based on the AJAX Web Programming Techniques | p. 97 |
Introduction | p. 97 |
Internet Programming with Asynchronous Javascript and XML | p. 98 |
System Architecture | p. 98 |
The User-Interface (UI) | p. 99 |
The Query-Transmitter | p. 101 |
The Results-Collector | p. 102 |
The Local Repository and XML Handler | p. 103 |
The Meta-Results Handler | p. 103 |
Retrieving Images with Human Appearance on the Web | p. 105 |
A Case Study | p. 105 |
The Meta-Search Engine Performance | p. 109 |
Asynchronous-Synchronous Analysis Performance | p. 111 |
Conclusions: Future Considerations | p. 112 |
References | p. 115 |
A Rule-Based Adaption Model for Ontology-Based Personalization | p. 117 |
Introduction | p. 117 |
Overview of Adaptation Approaches | p. 118 |
State-of-the-Art | p. 119 |
On the Use of Ontologies and Rules for Adaptation | p. 119 |
ODAS - A Domain Ontology for Adaptive Hypermedia Systems | p. 121 |
A Rule-Based Adaptation Model | p. 122 |
Applying Rules-Based Adaptation to a Portal | p. 122 |
A Formal Definition of the Adaptation Model | p. 125 |
ODAS-Based Instantiations of the Adaptation Model | p. 126 |
Implementation and Discussion | p. 131 |
Related Work | p. 132 |
Conclusion | p. 133 |
References | p. 134 |
Management and Processing of Personalized Annotations in Image Retrieval Systems | p. 137 |
Motivation | p. 137 |
Image Annotation Process | p. 139 |
Multi-level Annotation Model | p. 140 |
Subjectivity in Image Annotations | p. 142 |
Components of the Annotation Analysis Framework | p. 143 |
Graph Representation for Multi-level Annotations | p. 144 |
Relations Between Terms of Annotation | p. 148 |
Extending the Probabilistic Annotation by Multi-level Annotations | p. 149 |
Example of Context-Based Similarity | p. 151 |
Related Work | p. 152 |
Summary and Future Work | p. 153 |
References | p. 153 |
An Incremental Framework for Adapting the Hypermedia Structure of Multimedia Documents | p. 157 |
Introduction | p. 157 |
Multimedia Document Specification | p. 158 |
Semantic Adaptation of Multimedia Documents | p. 159 |
Adaptation of the Hypermedia Dimension | p. 162 |
Adaptation Based on the Hypermedia Structure | p. 165 |
Generating the Multimedia Document Sub-Specifications According to the Hypermedia Structure | p. 166 |
Adapting All Sub-Specifications at Once | p. 166 |
Adapting Sub-Specifications Step by Step | p. 168 |
Implementation | p. 169 |
Application to Concrete Multimedia Documents | p. 170 |
Concrete Multimedia Documents Adaptation | p. 171 |
Prototype | p. 172 |
Related Work | p. 173 |
Conclusion | p. 174 |
References | p. 175 |
Improving the Adaptiveness of an e-Learning System | p. 177 |
Introduction | p. 177 |
Web-Based Intelligent Education Systems | p. 178 |
Medical Education | p. 178 |
Cognitive Flexibility Theory | p. 179 |
The Motivation | p. 180 |
The COFALE Environment | p. 181 |
Extending COFALE | p. 182 |
Domain Knowledge | p. 182 |
Test Creation | p. 182 |
Student Assessment | p. 185 |
Architecture and Implementation Aspects | p. 188 |
System Evaluation | p. 190 |
Related Work | p. 192 |
Conclusions | p. 194 |
References | p. 195 |
The Context Oriented Architecture: An Augmentation of Context Awareness and Reactivity into Web Services | p. 199 |
Introduction | p. 199 |
Related Work | p. 201 |
Context Defined | p. 201 |
OWL-S: The Semantic Web Service Ontology Language | p. 203 |
Context Awareness Infrastructures | p. 204 |
Context Aware Web Services | p. 204 |
The Context Oriented Architecture | p. 206 |
The Negotiator | p. 208 |
The Context Sensors | p. 208 |
The Monitor | p. 208 |
The Context Response | p. 208 |
The Response Manager | p. 209 |
The Component Registry | p. 209 |
The Context Repository | p. 209 |
Usage Scenario | p. 210 |
OWL-S Extension | p. 211 |
Profile Ontology Extension | p. 212 |
Monitors Attribute | p. 212 |
Uses Attribute | p. 212 |
Responds Attribute | p. 213 |
Process Model Extension | p. 213 |
Exposes Attribute in the Process Model | p. 214 |
Results and Analysis: The File Storage Scenario | p. 215 |
Scenario Context | p. 215 |
Scenario Formalization in the Framework | p. 216 |
Semantic Model | p. 216 |
Interaction Model | p. 216 |
Conclusion | p. 218 |
References | p. 219 |
Knowledge-Assisted Analysis of Video for Content-Adaptive Coding and Transmission | p. 221 |
Introduction | p. 221 |
Domain Knowledge | p. 224 |
Knowledge-Assisted Video Analysis | p. 226 |
Color and Motion Initial Segmentation | p. 226 |
Low-level Descriptors Extraction | p. 227 |
Genetic Algorithm | p. 228 |
Content-Adaptive Coding and Transmission | p. 230 |
Basic Problem Formulation | p. 230 |
Channel Rate Optimization for Wireless Transmission Scenarios | p. 232 |
Experimental Results | p. 235 |
Conclusions | p. 238 |
References | p. 238 |
Mobile Photography within a Social Context | p. 241 |
Introduction | p. 241 |
Related Work | p. 244 |
Case Study | p. 245 |
Using PhotoFOAF for Social Photo Management | p. 247 |
Photo Production Phase | p. 247 |
Photo Consumption Phase | p. 248 |
Determining Social Relevance | p. 250 |
Embedded Metadata | p. 254 |
System architecture | p. 255 |
Social Network Visualization Experiments | p. 256 |
Conclusions and Future Work | p. 258 |
References | p. 259 |
An Adaptive Semantic Framework to Support Multiple User Viewpoints over Multiple Databases | p. 261 |
Introduction | p. 261 |
Information Heterogeneity | p. 262 |
Outline of the Chapter | p. 263 |
Related Work | p. 263 |
Logical Data Views vs. User Views | p. 263 |
Integrating Semantics, Rules, Logic and Databases | p. 265 |
A Multiple Viewpoint Semantic Framework | p. 267 |
Viewpoint Conceptualisation | p. 269 |
Semantic Mapping | p. 270 |
The Process to Project a Viewpoint | p. 271 |
Modelling Individual Users | p. 273 |
View-Based Query Answering and Result Adjustment | p. 274 |
Applying Preference and Rules in Query Answering | p. 277 |
User-Centre Query Answering | p. 278 |
Implementation and Validation | p. 280 |
Conclusions and Further Work | p. 282 |
References | p. 283 |
User Preferences for Access to Textual Information: Model, Tools and Experiments | p. 285 |
Introduction | p. 285 |
Motivations | p. 286 |
Textual Information and Users' Point of View | p. 286 |
Visual and Interactive Tools for Access to Textual Information | p. 287 |
Our Approach | p. 289 |
Models and Tools | p. 289 |
LUCIA: A Model for Representing User's Knowledge on Domains | p. 289 |
User-Centred Tools | p. 291 |
Experiment 1: Accessing Information | p. 294 |
Context and Materials | p. 294 |
Results and Discussion | p. 295 |
Experiment 2: Conceptual Metaphors | p. 298 |
Constraints on the Model for Metaphor Characterisation | p. 298 |
Map and Texts "Metaphoricity" | p. 300 |
Conclusion | p. 302 |
References | p. 303 |
Modeling the Reusable Content of Adaptive Web-Based Applications Using an Ontology | p. 307 |
Introduction | p. 307 |
Related Work | p. 309 |
Content Representation | p. 309 |
Content Transformation | p. 310 |
Development of Reusable Content | p. 311 |
The Method for Domain Modeling | p. 312 |
Importing Existing Domain Model Ontologies | p. 314 |
Delivering Ontology Content into Existing Adaptive Application | p. 315 |
Ontology Models of the Content | p. 316 |
Core Ontology of Content Model | p. 316 |
Domain and User Models Interconnection | p. 321 |
Meta-Model of the Adaptive Application Content | p. 322 |
Evaluation of Proposed Method | p. 322 |
Conclusions | p. 325 |
References | p. 325 |
Indexing and Browsing of Color Images: Design Considerations | p. 329 |
Introduction | p. 329 |
Color Descriptors and Similarity Measures | p. 331 |
Histogram and Dominant Color | p. 331 |
Distance Metrics | p. 332 |
Indexing and Dimensionality | p. 334 |
Limits of kd-Tree Effectiveness | p. 335 |
Point Configurations | p. 335 |
MDS and FastMap | p. 337 |
Browsing | p. 337 |
Efficiency of FastMap Configurations | p. 338 |
Conclusions | p. 343 |
References | p. 345 |
Generic Personal Assistance Architecture for Mobile Environments | p. 347 |
Introduction | p. 347 |
Related Work | p. 348 |
Personal Task Model | p. 350 |
Personal Assistant | p. 352 |
Goal Description | p. 353 |
Situation Influence by Task Execution | p. 354 |
Task Generation | p. 355 |
Situation Dependent Task Suggestion | p. 357 |
Control Circuit | p. 358 |
Personal Assistance Architecture | p. 358 |
Proof of Concept-Applications | p. 360 |
xGuide: Electronic Exhibition Guide | p. 360 |
Applied Task Definition | p. 361 |
StepMan | p. 361 |
Personal Assistant DiaTrace | p. 363 |
Mobile Personal Trainer | p. 365 |
Outcome Analysis | p. 366 |
Conclusion and Further Work | p. 367 |
References | p. 367 |
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