Mugellini / Sokhn / Szczepaniak Advances in Intelligent Web Mastering - 3

Proceedings of the 7th Atlantic Web Intelligence Conference, AWIC 2011, Fribourg, Switzerland, January, 2011
1. Auflage 2011
ISBN: 978-3-642-18029-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 86, 238 Seiten, eBook

Reihe: Advances in Intelligent and Soft Computing

The Atlantic Web Intelligence Conference brings together scientists, engineers, computer users, and students to exchange and share their experiences, new ideas, and research results about all aspects (theory, applications and tools) of intelligent methods applied to Web based systems, and to discuss the practical challenges encountered and the solutions adopted. Previous AWIC events were held in Spain – 2003, Mexico – 2004, Poland – 2005, Israel – 2006, France – 2007 and Czech Rep. – 2009.The present 7th Atlantic Web Intelligence Conference (AWIC’2011) was held during January 26-28, 2011, at the University of Applied Sciences of Fribourg, Switzerland. AWIC2011 is organized by the Multimedia Information System Group (MISG), Institute of the Technologies of Information and Communication (iTIC) of the University of Applied Sciences of Fribourg.

Zielgruppe

Research

Autoren/Hrsg.

Sokhn, Maria

Mugellini, Elena

Szczepaniak, Piotr S.

Chiara Pettenati, Maria

Inhaltsverzeichnis

1;Title Page;1
2;Preface;5
3;Contents;6
4;Part I Invited Lectures;9
4.1;Fuzzy Ontologies and Fuzzy Markup Language: A Novel Vision inWeb Intelligence;10
4.1.1;Introduction;10
4.1.2;Fuzzy Ontologies and Fuzzy Markup Language;11
4.1.2.1;Fuzzy Ontologies;11
4.1.2.2;Fuzzy Markup Language;12
4.1.3;Fuzzy Ontologies and FML: Real-World Applications;13
4.1.4;Conclusion and Future Works;16
4.1.5;References;16
4.2;Loose Ontological Coupling and the Social Semantic Web;18
4.2.1;Introduction;18
4.2.2;Loosely-Coupled Ontologies;19
4.2.3;Emergent Semantics;20
4.2.4;Conclusions;21
4.2.5;References;21
5;Part II Regular Papers;23
5.1;Further Experiments in Sentiment Analysis of French Movie Reviews;24
5.1.1;Introduction;24
5.1.2;Previous Work;25
5.1.3;FeatureDesign;26
5.1.3.1;Lexical Features;26
5.1.3.2;Morpho-syntactic Features;26
5.1.3.3;Semantic Features;27
5.1.4;Experiments;28
5.1.4.1;Results and Discussion;28
5.1.5;Conclusions;32
5.1.6;References;32
5.2;Querying over Heterogeneous and Distributed Data Sources;34
5.2.1;Introduction;34
5.2.2;Related Works;35
5.2.3;Virtual-Q System;37
5.2.3.1;Virtual Query Engine Architecture;38
5.2.3.2;Query Process;39
5.2.4;Prototype;41
5.2.5;Conclusion and Future Work;42
5.2.6;References;43
5.3;Experiments in Bayesian Recommendation;44
5.3.1;Introduction;44
5.3.2;Related Work;45
5.3.3;Notation;45
5.3.4;Bayesian Recommendation;45
5.3.5;Multinomial Model;46
5.3.5.1;Dirichlet Prior;46
5.3.6;Gaussian Model;47
5.3.7;Experiments;49
5.3.7.1;Evaluation Metrics;49
5.3.7.2;Results;49
5.3.7.3;Sparsity;50
5.3.8;Conclusions;52
5.3.8.1;Future Work;52
5.3.9;References;52
5.4;Experiences of Knowledge Visualization in Semantic Web Applications;54
5.4.1;Introduction;54
5.4.2;Knowledge Visualization in the Semantic Web Context;55
5.4.2.1;EasyOnto;56
5.4.3;Integrated Environments for Knowledge Management and Visualization;58
5.4.3.1;IRCS Framework;59
5.4.3.2;The AWI Environment;61
5.4.4;Conclusions;63
5.4.5;References;63
5.5;“Tagsonomy”: Easy Access to Web Sites through a Combination of Taxonomy and Folksonomy;65
5.5.1;Introduction;66
5.5.2;Web Access through Taxonomies and Folksonomies;66
5.5.3;Combining the Taxonomy and Folksonomy Approaches;67
5.5.4;The Easy Access (EA) Project;68
5.5.4.1;Test Case: Applying the EA Tagsonomy to a Web Site;70
5.5.4.2;Preliminary Evaluation;72
5.5.5;Conclusions;73
5.5.6;References;74
5.6;Conceptual Query Expansion and Visual Search Results Exploration forWeb Image Retrieval;76
5.6.1;Introduction;76
5.6.2;Related Work;78
5.6.3;Conceptual Query Expansion for Image Search;79
5.6.3.1;Extracting Concepts from Wikipedia;79
5.6.3.2;Ranking the Extracted Concepts;80
5.6.3.3;Generating Expanded Queries;81
5.6.4;Visual and Conceptual Search Results Exploration;81
5.6.4.1;Multi-resolution SOM-Based Image Organization;82
5.6.4.2;Concept Hierarchy Focusing and Filtering;82
5.6.5;Conclusions and Future Work;84
5.6.6;References;84
5.7;Memoria-Mea: Combining Semantic Technologies and Interactive Visualization Techniques for Personal Information Management;86
5.7.1;Introduction;86
5.7.2;Related Work;87
5.7.3;Memoria-Mea: Logical Architecture;88
5.7.4;Memoria-Mea: Technical Architecture;88
5.7.5;Prototype;90
5.7.5.1;Visualization Module: MemoSIV;91
5.7.5.2;Annotation Module: MemoSAM;92
5.7.6;Conclusion and Future Works;94
5.7.7;References;94
5.8;Cylindric Extensions of Fuzzy Sets. An Application to Linguistic Summarization of Data;96
5.8.1;Introduction;96
5.8.1.1;The Definitions of Fuzzy Sets and Their Cylindric Extensions;97
5.8.1.2;Linguistic Summaries of Databases;97
5.8.2;Compound Linguistic Expressions Represented by Cylindric Extensions of Fuzzy Sets;98
5.8.3;Summaries with Compound Summarizers;99
5.8.4;Summaries with Qualifiers;100
5.8.5;Quality Measures;100
5.8.5.1;Defining Degree of Covering via Cylindric Extensions;101
5.8.5.2;Defining Degree of Appropriateness Using Cylindric Extensions;102
5.8.6;Conclusions;102
5.8.7;References;103
5.9;Comparison of Selected Methods for Document Clustering;104
5.9.1;Introduction;104
5.9.2;Applied Methods of Cluster Analysis;105
5.9.2.1;Similarity Measure;106
5.9.2.2;Clustering Criterion Functions;106
5.9.2.3;Clustering Methods;106
5.9.2.4;Quality Measures;108
5.9.2.5;External Quality Measures;108
5.9.3;The 20 Newsgroups Data Set;109
5.9.4;Steps of Prepared Data and Their Analyses;109
5.9.5;Comparison of Clustering Methods;110
5.9.6;Description of Obtained Clusters;111
5.9.7;Conclusion;112
5.9.8;References;113
5.10;Speech Indexation in REPLAY;114
5.10.1;Introduction;114
5.10.2;Context;115
5.10.3;Speech-To-Text Plug-In;116
5.10.3.1;Speech Indexation Technologies;116
5.10.3.2;Storage of Audio Isochronic Metadata;118
5.10.3.3;Storage in REPLAY;118
5.10.4;Audio Transcription Enhancement;119
5.10.5;Relevance Value: Algorithm Concepts;120
5.10.6;Prototype;121
5.10.7;Conclusion and Future Works;122
5.10.8;References;122
5.11;DegExt – A Language-Independent Graph-Based Keyphrase Extractor;123
5.11.1;Introduction;123
5.11.2;DegExt — Degree-Based Extractor;125
5.11.3;Experimental Results;128
5.11.4;Conclusions and Future Work;131
5.11.5;References;132
5.12;Verifying Authenticity in Interactive Behaviors of SemanticWeb Services;133
5.12.1;Introduction;133
5.12.2;OWL Ontology ased Past-LTL and Reasoning;135
5.12.2.1; The ALCQIO f ragment of OWL;135
5.12.2.2;Conceptualizing Assertion Change;136
5.12.2.3;Reducing;137
5.12.3;Authenticity in Past-LTL;140
5.12.4;RelatedWorks;141
5.12.5;Conclusions and FutureWorks;142
5.12.6;References;142
5.13;SMAC: Smart Multimedia Archiving for Conferences;144
5.13.1;Introduction;144
5.13.2;Algorithm Overview;145
5.13.3;Preliminary Considerations about Slides Pictures;146
5.13.4;Video Segmentation;146
5.13.5;Matching Refinement;147
5.13.5.1;Frames Identification;147
5.13.5.2;Identification Refinement;147
5.13.5.3;Orphan Sequences Assignment;149
5.13.6;Results;149
5.13.6.1;Video Transitions Detection Result;150
5.13.6.2;Matching Refinement Result;150
5.13.7;Conclusion and Future Works;152
5.13.8;References;152
5.14;Ontological-Based Information Extraction of Construction Tender Documents;154
5.14.1;Introduction;154
5.14.2;Related Works;156
5.14.3;Ontological-Based Information Extraction Processes;157
5.14.3.1;Document Structure Ontology;157
5.14.3.2;Document Preprocessing;159
5.14.3.3;Information Acquisition;159
5.14.4;Experimental Setup;160
5.14.5;Result and Evaluation;161
5.14.6;Conclusion;162
5.14.7;References;162
5.15;Using Level-2 Fuzzy Sets to Combine Uncertainty and Imprecision in Fuzzy Regions;164
5.15.1;Introduction;164
5.15.2;Preliminaries;165
5.15.2.1;Fuzzy Regions;165
5.15.2.2;Limitations;168
5.15.3;Fuzzy Powerset Extension;168
5.15.3.1;Concept;168
5.15.3.2;Definition;169
5.15.3.3;Interpretation;169
5.15.4;Conclusion;172
5.15.5;References;173
5.16;Evaluation of Categorical Data Clustering;174
5.16.1;Introduction;174
5.16.2;Evaluation Criteria of Clustering;176
5.16.2.1;Variability Measures for Nominal Variables;176
5.16.2.2;Variability Measures Based Evaluation Criteria of Clustering;177
5.16.3;Example;179
5.16.4;Conclusion;182
5.16.5;References;182
5.17;Enabling Product Comparisons on Unstructured Information Using Ontology Matching;184
5.17.1;Introduction;184
5.17.2;Ontology Matching;185
5.17.2.1;Element-Level Matchers;186
5.17.2.2;Instance Matching;187
5.17.3;Semantic Integration of Product Specifications;187
5.17.3.1;Domain Model;188
5.17.3.2;Product Specification Normalization;189
5.17.4;Similarity Measures;190
5.17.5;Evaluation;192
5.17.6;Conclusions;193
5.17.7;References;194
5.18;Analyzing Sentiment in a Large Set of Web Data While Accounting for Negation;195
5.18.1;Introduction;195
5.18.2;Sentiment Analysis;196
5.18.3;Sentiment Negation;199
5.18.3.1;Framework;199
5.18.3.2;Implementation;201
5.18.3.3;Evaluation;201
5.18.4;Conclusions and Future Work;203
5.18.5;References;204
5.19;A Quality Assurance Framework for Ontology Construction and Refinement;206
5.19.1;Introduction;206
5.19.2;A Framework for Form-Based Ontology Evaluation;207
5.19.2.1;Ontology Editing Assistance;208
5.19.2.2;Consistency Verification after Ontology Editing;208
5.19.2.3;Evaluation of Ontology Editing Assistance;208
5.19.3;A Method for Content-Based Evaluation;210
5.19.3.1;Application to Construction of Sustainability Science Ontology;210
5.19.3.2;Concept Map Generation in Construction of Clinical Ontology;211
5.19.4;Related Work;213
5.19.5;Conclusion;214
5.19.6;References;215
5.20;Location-Based Web System for Geographically Distributed Mobile Teamwork Management;216
5.20.1;Introduction;216
5.20.2;The High-Level Architecture of the System;218
5.20.3;The Main Components and Technologies;218
5.20.3.1;Client Components and Technologies;218
5.20.3.2;Server Components and Technologies;220
5.20.4;Typical Usage of the Teamwork Tasks Management Application;221
5.20.5;Conclusion;222
5.20.6;References;222
5.21;Two New Methods for Network Analysis: Ant Colony Optimization and Reduction by Forgetting;224
5.21.1;Introduction;224
5.21.2;Ant Colony Optimization;225
5.21.2.1;Implicit Relevance Based Inquirer Model;225
5.21.3;Forgetting Curve;226
5.21.3.1;Forgetting of Social Network;229
5.21.4;Experiments;229
5.21.5;Conclusions;233
5.21.6;References;233
6;Author Index;234