E-Book, Englisch, Band 24, 1010 Seiten
Filipe / Aalst / Cordeiro Enterprise Information Systems
2009
ISBN: 978-3-642-01347-8
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
11th International Conference, ICEIS 2009, Milan, Italy, May 6-10, 2009, Proceedings
E-Book, Englisch, Band 24, 1010 Seiten
Reihe: Lecture Notes in Business Information Processing
ISBN: 978-3-642-01347-8
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
This books contains the proceedings of the 11th International Conference on Enterprise Information Systems, ICEIS 2009, held in Milan, Italy, in May 2009. The 81 papers presented were carefully reviewed and selected from 644 submissions. The topics covered are: databases and information systems integration, artificial intelligence and decision support systems, information systems analysis and specification, software agents and internet computing, and human-computer interaction.
Autoren/Hrsg.
Weitere Infos & Material
1;Preface;5
2;Organization;6
3;Table of Contents;12
4;Part I Databases and Information Systems Integration;19
4.1;MIDAS: A Middleware for Information Systems with QoS Concerns;20
4.1.1;Introduction;20
4.1.1.1;Contributions;21
4.1.2;MIDAS Architecture;22
4.1.2.1;Code Modifications;24
4.1.3;Tx Estimation;24
4.1.4;Experiments;25
4.1.4.1;Workload Composition;25
4.1.5;Results;25
4.1.6;Related Work;28
4.1.7;Conclusions and Future Works;29
4.1.8;References;29
4.2;Instance-Based OWL Schema Matching;31
4.2.1;Introduction;31
4.2.2;OWL Schema Matching;32
4.2.2.1;OWL Extralite;32
4.2.2.2;Vocabulary Matchings and Concept Mappings;34
4.2.2.3;Consistent OWL Matchings;36
4.2.3;Instance-Based OWL Schema Matching;37
4.2.4;Experimental Results;40
4.2.5;Conclusions;42
4.2.6;References;42
4.3;The Integrative Role of IT in Product and Process Innovation: Growth and Productivity Outcomes for Manufacturing;44
4.3.1;Introduction;44
4.3.2;Assimilation of IT for Business Process Integration;45
4.3.3;Research Model and Hypotheses;46
4.3.4;Research Method;47
4.3.4.1;Data Collection;47
4.3.4.2;Measurement;48
4.3.4.3;Sample;48
4.3.5;Results;49
4.3.5.1;Estimation of Model Parameters;49
4.3.5.2;Test of Research Hypotheses;51
4.3.6;Discussion and Conclusions;52
4.3.7;References;54
4.4;Vectorizing Instance-Based Integration Processes;57
4.4.1;Introduction;57
4.4.2;Problem Description;58
4.4.2.1;Assumptions and Requirements;58
4.4.2.2;Optimization Problem;59
4.4.2.3;Solution Overview;60
4.4.3;Rewriting Process Plans;61
4.4.3.1;Message Model and Process Model;61
4.4.3.2;Rewriting Algorithm;62
4.4.3.3;Cost-Based Vectorization;65
4.4.4;Experimental Evaluation;65
4.4.4.1;Experimental Setup;66
4.4.4.2;Performance and Throughput;66
4.4.5;Related Work;67
4.4.6;Conclusions;68
4.4.7;References;68
4.5;Invisible Deployment of Integration Processes;70
4.5.1;Introduction;70
4.5.2;Vision Overview;71
4.5.2.1;Assumptions and Hypotheses;71
4.5.2.2;Conceptual Architecture;72
4.5.2.3;Problems and Challenges;73
4.5.3;Deployment;74
4.5.3.1;Integration Process Generation;74
4.5.3.2;Candidate Set Determination;75
4.5.4;Runtime;77
4.5.4.1;Platform-Independent Cost Model and Cost Normalization;77
4.5.4.2;Optimality Decision;78
4.5.4.3;Heterogeneous Load Balancing;78
4.5.5;System Architecture;79
4.5.6;Related Work;80
4.5.6.1;Application Areas;80
4.5.6.2;Virtualization Approaches;81
4.5.7;Summary;81
4.5.8;References;81
4.6;Customizing Enterprise Software as a Service Applications: Back-End Extension in a Multi-tenancy Environment;83
4.6.1;Introduction;83
4.6.2;Related Work;84
4.6.3;Modes of Customization;85
4.6.3.1;Desktop Integration;85
4.6.3.2;User Interface Customization;85
4.6.3.3;Back-End Customization;85
4.6.3.4;Problem Statement;86
4.6.3.5;Show Case;86
4.6.4;Implementation;87
4.6.4.1;Dynamic Instance Composition;88
4.6.4.2;Partner Context Activities;91
4.6.5;Conclusions;93
4.6.6;References;93
4.7;Pattern-Based Refactoring of Legacy Software Systems;95
4.7.1;Introduction;95
4.7.2;Legacy Software Transformation;97
4.7.2.1;Incremental Software Transformation;97
4.7.2.2;TransFormr;98
4.7.3;Pattern-Based Moving of MemberGroups;99
4.7.4;Experimental Analysis;102
4.7.5;Related Work;103
4.7.6;Conclusions;104
4.7.7;References;105
4.8;A Natural and Multi-layered Approach to Detect Changes in Tree-Based Textual Documents;107
4.8.1;Introduction;107
4.8.2;Related Works;108
4.8.3;Naturalness in Diff-ing Literary Documents;109
4.8.3.1;A New Set of Natural Operations;110
4.8.4;An Optimized Algorithm for Natural (XML) Diff-ing: JNDiff;112
4.8.5;Expressing Detected Changes: JNMerge and JNApply;114
4.8.6;Computational Complexity of JNDiff and JNMerge;115
4.8.7;A Practical Application: Detecting Changes in Legislative Documents;116
4.8.8;Conclusions;117
4.8.9;References;117
4.9;CrimsonHex: A Service Oriented Repository of Specialised Learning Objects;119
4.9.1;Introduction;119
4.9.2;State of Art;120
4.9.3;Specialised Learning Objects;122
4.9.4;Architecture;123
4.9.4.1;Components;123
4.9.4.2;Functions;124
4.9.4.3;Communication Model;125
4.9.5;Implementation;126
4.9.5.1;Storage;126
4.9.5.2;Validation;127
4.9.5.3;Interface;127
4.9.5.4;Security;128
4.9.6;Tests and Evaluation;128
4.9.7;Conclusions;129
4.9.8;References;130
4.10;A Scalable Parametric-RBAC Architecture for the Propagation of a Multi-modality, Multi-resource Informatics System;131
4.10.1;Introduction;131
4.10.2;Organizational Structure of a Center;133
4.10.3;The X-MIMI Architecture;134
4.10.3.1;X-MIMI System Components;134
4.10.3.2;Data/Information Flow;135
4.10.3.3;Parametric Administrative RBAC;136
4.10.3.4;WYDIWYS Web Inferface;138
4.10.3.5;Role-Based Testing;139
4.10.3.6;Experimental Results;139
4.10.4;Conclusions;140
4.10.5;References;141
4.11;Minable DataWarehouse;142
4.11.1;Introduction;142
4.11.2;Basic Concepts;144
4.11.2.1;Data Warehouses;144
4.11.2.2;Association Rule Mining;145
4.11.2.3;Example;146
4.11.3;Data Mining without a Data Warehouse;146
4.11.4;Data Mining with a DataWarehouse;147
4.11.5;Proposed Framework: Minable DataWarehouse;148
4.11.5.1;Design Decision;149
4.11.6;Demonstration;150
4.11.6.1;Input Files: Instant Messaging Files;150
4.11.6.2;Input to the Data Mining Tool:Weka;151
4.11.6.3;Files Viewed onWeka;151
4.11.6.4;Generated Association Rules;152
4.11.7;Conclusions and Future Work;153
4.11.8;References;153
4.12;A Step Forward in Semi-automatic Metamodel Matching: Algorithms and Tool;154
4.12.1;Introduction;154
4.12.2;Background;155
4.12.2.1;Model Driven Engineering;155
4.12.2.2;Mapping Specification and Transformation Definition;156
4.12.2.3;Tools forModel Matching;156
4.12.3;Proposed Approach for Metamodel Matching;156
4.12.3.1;Foundation for Metamodel Matching;157
4.12.3.2;Another Algorithm for Metamodel Matching;157
4.12.4;Extending and Adapting the SAMT4MDE;161
4.12.4.1;Modeling;161
4.12.4.2;Prototyping;163
4.12.5;Tests;163
4.12.6;Conclusions;164
4.12.7;References;165
4.13;A Study of Indexing Strategies for Hybrid Data Spaces;166
4.13.1;Introduction;166
4.13.2;The Extended Hybrid Indexing;167
4.13.2.1;Hybrid Geometric Concepts and Normalization;167
4.13.2.2;Extending the ND-Tree to the HDS;167
4.13.2.3;Enhanced Strategy for Prioritizing Discrete/Continuous Dimensions;168
4.13.3;Experimental Results;169
4.13.3.1;Experimental Setup;169
4.13.3.2;Performance Gain with Increasing Database Sizes;170
4.13.3.3;Performance for Various Additional Dimensions;170
4.13.3.4;Performance for Different Alphabet Sizes;171
4.13.3.5;Performance for Different Query Box Sizes;171
4.13.3.6;Effect of Enhanced Strategy with Power Value Adjustment;172
4.13.4;Performance Estimation Model;172
4.13.5;Conclusions;175
4.13.6;References;176
4.14;Relaxing XML Preference Queries for Cooperative Retrieval;177
4.14.1;Introduction;177
4.14.2;XML Preference Queries;178
4.14.3;Relaxing Queries Based on Structural Patterns;180
4.14.4;Ordering Relaxations;181
4.14.5;Dealing with Multiple Preferences;183
4.14.6;Design of IPX;184
4.14.7;Related Work;186
4.14.8;Conclusions;187
4.14.9;References;187
4.15;DeXIN: An Extensible Framework for Distributed XQuery over Heterogeneous Data Sources;189
4.15.1;Introduction;189
4.15.2;Application Scenario;191
4.15.3;Related Work;192
4.15.4;DeXIN;193
4.15.4.1;Architectural Overview;193
4.15.4.2;Query Evaluation Process;193
4.15.5;XQuery Extension to SPARQL;195
4.15.6;Implementation and Experiments;197
4.15.6.1;Experimental Application:Web Service Management;197
4.15.6.2;Performance Analysis;197
4.15.7;Conclusions and Future Work;199
4.15.8;References;200
4.16;Dimensional Templates in Data Warehouses: Automating the Multidimensional Design of Data Warehouse Prototypes;201
4.16.1;Introduction;201
4.16.2;Related Work;203
4.16.3;Dimensional Templates;204
4.16.3.1;The Overall Concept;204
4.16.3.2;Building Dimensional Templates;204
4.16.3.3;Rationale Diagrams;206
4.16.4;Using Dimensional Templates;208
4.16.4.1;Step 1: Finding Mappable Markers;209
4.16.4.2;Step 2: Mapping Markers;209
4.16.4.3;Step 3: Determining Usable Markers;209
4.16.4.4;Step 4: Determining Satisfied Goals;209
4.16.4.5;Step 5: Multidimensional Generation;210
4.16.5;Conclusions;211
4.16.6;References;211
4.17;Multiview Components for User-Aware Web Services;213
4.17.1;Introduction;213
4.17.2;User-Aware Web Services: A Running Scenario;214
4.17.3;The Multiview Component Model for User-Aware Web Services;215
4.17.3.1;Preliminary 1: The Component Concept;215
4.17.3.2;Preliminary 2: The View Concept;215
4.17.3.3;The VUML Multiview Component Model;216
4.17.4;From Multiview Component to User-Aware Web services: A Rule Based Approach;217
4.17.4.1;From the Multiview Component Based PIM to MVWSDL Code;218
4.17.4.2;From Multiview Component Model to Java Code;221
4.17.5;Related Works;222
4.17.6;Conclusions;223
4.17.7;References;224
4.18;Knowledge Based Query Processing in Large Scale Virtual Organizations;225
4.18.1;Introduction;225
4.18.2;Virtual Organizations Data Profile;226
4.18.3;Related Work;228
4.18.3.1;Distributed Enterprise Databases;228
4.18.3.2;Internet Communities;228
4.18.4;Semantic Query Processing;229
4.18.4.1;Ontology Knowledge Base;229
4.18.4.2;Query Execution Using VO’s Knowledge Base;231
4.18.5;Knowledge Facts Obtention;233
4.18.6;QPro2E Analysis;234
4.18.7;Conclusions;235
4.18.8;References;235
4.19;Applying Recommendation Technology in OLAP Systems;237
4.19.1;Introduction;237
4.19.1.1;Context and Motivations;237
4.19.1.2;Related Work;238
4.19.1.3;Aims and Contributions;238
4.19.2;Decision-Support Analysis;239
4.19.2.1;Multidimensional Data Model;239
4.19.2.2;OLAP Analysis Modelling;240
4.19.3;Flexible Recommendations in OLAP;242
4.19.4;Preference-Based Recommendation Framework;244
4.19.4.1;User Preferences Modelling;244
4.19.4.2;Recommendation Generation;245
4.19.4.3;Recommendation Display;247
4.19.4.4;Example;247
4.19.5;Conclusions;249
4.19.6;References;249
4.20;Classification and Prediction of Software Cost through Fuzzy Decision Trees;251
4.20.1;Introduction;251
4.20.2;Brief Literature Review;253
4.20.3;Methodology;253
4.20.3.1;Cost Factors Description;254
4.20.3.2;Fuzzy Decision Trees and Classification Rules;255
4.20.3.3;Design of the Experiments;256
4.20.4;Empirical Experiments and Results;260
4.20.5;Conclusions;262
4.20.6;References;263
4.21;s-OLAP: Approximate OLAP Query Evaluation on Very Large Data Warehouses via Dimensionality Reduction and Probabilistic Synopses;265
4.21.1;Introduction;265
4.21.2;s-OLAP: An Overview;267
4.21.3;KS-Tree: A Synopsis Data Structure for OLAP;269
4.21.3.1;Building and Querying Probabilistic Synopses;269
4.21.3.2;KS-Tree Data Engineering Overview;271
4.21.4;s-OLAP Query Model;272
4.21.5;Capturing and Handling the Dynamics of OLAP Queries;274
4.21.6;Experimental Assessment;275
4.21.7;Related Work;277
4.21.8;Conclusions and Future Work;278
4.21.9;References;278
5;Part II Artificial Intelligence and Decision Support Systems;280
5.1;A Self-learning System for Object Categorization;281
5.1.1;Introduction;281
5.1.2;Learning;283
5.1.2.1;LCA;286
5.1.3;Experiments and Results;288
5.1.4;Conclusions;290
5.1.5;References;290
5.2;A Self-tuning of Membership Functions for Medical Diagnosis;291
5.2.1;Introduction;291
5.2.2;Basic Concept of Fuzzy Logic;292
5.2.3;Decision Tree Learning;293
5.2.4;The Self-tuning Algorithm;294
5.2.4.1;Feature Selection;294
5.2.4.2;Automatic Membership Functions Generation;295
5.2.4.3;Membership Function Tuning;297
5.2.5;Experiment;298
5.2.5.1;Data Sets;298
5.2.5.2;Experimental Results;299
5.2.6;Conclusions;301
5.2.7;References;302
5.3;Insolvency Prediction of Irish Companies Using Backpropagation and Fuzzy ARTMAP Neural Networks;303
5.3.1;Introduction;303
5.3.2;Backpropagation Neural Networks;304
5.3.3;Fuzzy ARTMAP Neural Network Classifier;305
5.3.4;The Data;307
5.3.5;Empirical Results and Discussion;308
5.3.5.1;Prediction Accuracy;308
5.3.5.2;ROC Analysis;310
5.3.5.3;AUC;312
5.3.5.4;Validation of Results;313
5.3.6;Conclusions;313
5.3.7;References;313
5.4;Frequent Subgraph-Based Approach for Classifying Vietnamese Text Documents;315
5.4.1;Introduction;315
5.4.2;Related Work;316
5.4.3;Graph-Based Document Representation Model;317
5.4.4;Vietnamese Text Classification Based on Frequent Subgraphs;318
5.4.4.1;Pre-processing;318
5.4.4.2;Graph Construction;318
5.4.4.3;Representative Feature Extraction;319
5.4.4.4;Classification;319
5.4.5;Experimental Evaluation;320
5.4.6;Conclusions;322
5.4.7;References;323
5.5;Random Projection Ensemble Classifiers;325
5.5.1;Introduction;325
5.5.1.1;Random Projections;326
5.5.2;The Proposed Algorithm;327
5.5.3;Experimental Results;328
5.5.4;Conclusions and Future Work;330
5.5.5;References;330
5.6;Knowledge Reuse in Data Mining Projects and Its Practical Applications;333
5.6.1;Introduction;333
5.6.2;Literature Review;334
5.6.3;Knowledge Reuse Environment;335
5.6.4;Knowledge Reuse and Experimental Platform;336
5.6.4.1;Problem Characterization;336
5.6.5;Conclusions;339
5.6.6;References;340
5.7;Enhancing Text Clustering Performance Using Semantic Similarity;341
5.7.1;Introduction;341
5.7.2;Semantic Similarity Measures;342
5.7.3;Semantic Similarity Based Model (SSBM);343
5.7.4;Experimental Analysis;345
5.7.4.1;Datasets;345
5.7.4.2;Evaluation Measures;345
5.7.4.3;Results and Analysis;346
5.7.5;Conclusions;349
5.7.6;References;350
5.8;Stereo Matching Using Synchronous Hopfield Neural Network;352
5.8.1;Introduction;352
5.8.2;Scanline-Based Stereo Matching Problem;354
5.8.3;Proposed Method;356
5.8.3.1;Feature Extraction and Selection;356
5.8.3.2;Stereo Matching Using Synchronous Hopfield Neural Networks (SHNN);357
5.8.3.3;False Target Removing;358
5.8.4;Implementation;358
5.8.4.1;Experiment I – Determination of t$_{i}$ and a$_{i}$;359
5.8.4.2;Experiment II – Determination of d$_{max}$ and k;359
5.8.4.3;Verification and Benchmarking;360
5.8.5;Conclusions;361
5.8.6;References;361
5.9;Monotonic Monitoring of Discrete-Event Systems with Uncertain Temporal Observations;364
5.9.1;Introduction;364
5.9.2;Discrete-Event Systems;365
5.9.3;Diagnosis;366
5.9.4;Monitoring;369
5.9.4.1;Stratification;371
5.9.5;Conclusions;376
5.9.6;References;377
5.10;A Service Composition Framework for Decision Making under Uncertainty;379
5.10.1;Introduction;379
5.10.2;Understanding the Problem;382
5.10.3;Service Composition Framework;383
5.10.4;Optimization Semantics;386
5.10.5;A Case Study;387
5.10.6;Implementation Notes;389
5.10.7;Conclusions and Future Work;390
5.10.8;References;391
5.11;A Multi-criteria Resource Selection Method for Software Projects Using Fuzzy Logic;392
5.11.1;Introduction;392
5.11.2;Resource Selection and Knowledge Representation;393
5.11.2.1;Specifying Selection Criteria;394
5.11.2.2;Resource Selection Approaches;395
5.11.2.3;Evolving the Proposal;396
5.11.3;MRES – A Fuzzy Logic Based Approach;397
5.11.4;Prototype;401
5.11.5;Evaluation;402
5.11.6;Final Remarks and Future Work;403
5.11.7;References;404
5.12;An Optimized Hybrid Kohonen Neural Network for Ambiguity Detection in Cluster Analysis Using Simulated Annealing;405
5.12.1;Introduction;405
5.12.2;Self Organizing Map and Clustering;406
5.12.3;Incremental Clustering and Rough set Theory;407
5.12.3.1;Incremental Clustering;407
5.12.3.2;Combination of Rough Set Theory and Incremental Clustering;408
5.12.4;Simulated Annealing;410
5.12.5;Optimized Rough SOM Using Simulated Annealing;411
5.12.6;Experiments Results;413
5.12.7;Conclusions and Future Works;416
5.12.8;References;416
5.13;Interactive Quality Analysis in the Automotive Industry: Concept and Design of an Interactive, Web-Based Data Mining Application;418
5.13.1;Introduction;418
5.13.2;Interactivity Closes the Gap;420
5.13.2.1;Interactive Decision Trees;420
5.13.2.2;Other Interactive Mining Tasks;421
5.13.3;Architecture;422
5.13.3.1;Evolution of the Architecture;422
5.13.3.2;Interactive, Scalable Web Application;423
5.13.4;Interactive Web-Based Presentation Layer;425
5.13.5;Scalable Mining Backend;428
5.13.6;Conclusion and Future Work;429
5.13.7;References;430
5.14;NARFO Algorithm: Mining Non-redundant and Generalized Association Rules Based on Fuzzy Ontologies;431
5.14.1;Introduction;431
5.14.2;Related Work;432
5.14.3;NARFO Algorithm;433
5.14.3.1;Data Scanning;434
5.14.3.2;Identifying Similar Items;434
5.14.3.3;Generating Candidates;435
5.14.3.4;Calculating the Weight of Candidates;435
5.14.3.5;Evaluating Candidates;435
5.14.3.6;Generating Rules;436
5.14.3.7;Generalizing and Treating Redundancy;437
5.14.4;Experiments;438
5.14.5;Conclusions and Future Work;440
5.14.6;References;441
5.15;Automated Construction of Process Goal Trees from EPC-Models to Facilitate Extraction of Process Patterns;443
5.15.1;Introduction;443
5.15.2;Structures and Semantically Annotated EPC Models;447
5.15.2.1;Structured EPC Models;447
5.15.2.2;Automated Semantic Annotation;448
5.15.3;Process Goal Trees;449
5.15.4;Construction of Process Goal Trees;451
5.15.5;Related Work;454
5.15.6;Conclusions and Practical Experiences;456
5.15.7;References;457
6;Part III Information Systems Analysis and Specification;459
6.1;A Service Integration Platform for the Labor Market;460
6.1.1;Introduction;460
6.1.2;Background;461
6.1.3;Collaboration Services;461
6.1.3.1;The Business and Technological Approach;462
6.1.3.2;Consequences of Business Integration Needs;462
6.1.3.3;Services in the Interoperability Framework;463
6.1.4;Technology Description;463
6.1.4.1;Involving a New Node;465
6.1.4.2;An Example;466
6.1.5;Concluding Remarks;470
6.1.6;References;470
6.2;Developing Business Process Monitoring Probes to Enhance Organization Control;471
6.2.1;Introduction;471
6.2.2;Theoretical Background;472
6.2.2.1;The Balanced Scorecards;472
6.2.2.2;The GQM and Its Evolution to the GQM$^{+]$Strategy;473
6.2.2.3;The Business Motivation Model;473
6.2.3;The Case Study;474
6.2.3.1;Data Analysis;475
6.2.4;Developing the Probes for Our Case Study;477
6.2.5;The New Business and IT Set Up;479
6.2.6;Conclusions;480
6.2.7;References;481
6.3;Text Generation for Requirements Validation;482
6.3.1;Introduction;482
6.3.2;Related Works;483
6.3.3;Architecture and Dataflow of Our CASE Tool;484
6.3.4;Generate Natural Language Text from UML Model;487
6.3.4.1;The Approach;487
6.3.4.2;Document Planning;488
6.3.4.3;Mirco Planning;489
6.3.5;Case Study;489
6.3.6;Implementation;490
6.3.7;Example of the Text Generated for Validation;491
6.3.8;Achieved Results and Conclusions;491
6.3.9;References;492
6.4;Automatic Compositional Verification of Business Processes;494
6.4.1;Introduction;494
6.4.2;BP and BPTM Specification;495
6.4.3;Verification Approach;497
6.4.4;Case Study;499
6.4.4.1;Expected Behaviour Specification;500
6.4.4.2;TM Realization;501
6.4.4.3;TM Verification;502
6.4.4.4;Discussion of Results;503
6.4.5;Conclusions and Future Work;503
6.4.6;References;504
6.5;Actor Relationship Analysis for the i* Framework;506
6.5.1;Introduction;506
6.5.2;ARM;507
6.5.2.1;Overview;507
6.5.2.2;Actor Situation Matrix: ASM;508
6.5.2.3;Actor Relationship Matrix - ARM;508
6.5.2.4;Total Actor Relationship Matrix: ARM*;509
6.5.3;Example;510
6.5.3.1;ASM;510
6.5.3.2;ARM*;511
6.5.3.3;SD Model;511
6.5.4;Case Study;511
6.5.5;Discussion;512
6.5.5.1;Usefulness of ARM;513
6.5.5.2;Equivalence of SD Models Using ARM;513
6.5.5.3;Integration of SD Models with ARM;513
6.5.5.4;Correspondence between Situations and Inner Goals;514
6.5.6;Conclusions;514
6.5.7;References;515
6.6;Towards Self-healing Execution of Business Processes Based on Rules;516
6.6.1;Introduction;516
6.6.2;Related Work;517
6.6.3;The BP-FAMA Architecture;519
6.6.4;The RbBPDL Language;519
6.6.4.1;Use Case;521
6.6.5;Self-healing Execution of Business Processes;522
6.6.5.1;Exception Recognition;522
6.6.5.2;Exceptions Handling;524
6.6.6;Summary;526
6.6.7;References;527
6.7;Towards Flexible Inter-enterprise Collaboration: A Supply Chain Perspective;528
6.7.1;Introduction;528
6.7.2;Collaboration Approaches;530
6.7.3;Implications from the Supply Chain Perspective;532
6.7.4;Solution Directions;534
6.7.5;Example;538
6.7.6;Related Work;539
6.7.7;Conclusions;540
6.7.8;References;540
6.8;A Model-Based Tool for Conceptual Modeling and Domain Ontology Engineering in OntoUML;543
6.8.1;Introduction;543
6.8.2;Presentation of the Editor;545
6.8.2.1;Live Validation;545
6.8.2.2;Deriving Model Information;547
6.8.2.3;Batch Validation;548
6.8.3;The Architecture and Implementation of the Editor;550
6.8.4;Related Work;551
6.8.5;Final Considerations;551
6.8.6;References;552
6.9;Concepts-Based Traceability: Using Experiments to Evaluate Traceability Techniques;554
6.9.1;Introduction;554
6.9.2;Knowledge Engineering and UP;555
6.9.2.1;Ontological Engineering;556
6.9.2.2;Knowledge Engineering Discipline;556
6.9.3;Concepts-Based Traceability;558
6.9.3.1;ONTrace: A Tool for Concepts-Based Traceability;558
6.9.3.2;Related Work;559
6.9.4;The Experiment;559
6.9.4.1;Definition;559
6.9.4.2;Planning and Operation;560
6.9.4.3;Analysis and Interpretation;560
6.9.5;Experiment Replication;562
6.9.5.1;Definition, Planning and Operation;562
6.9.5.2;Analysis and Interpretation;563
6.9.6;Lessons Learned and Final Remarks;564
6.9.7;References;565
6.10;A Service-Oriented Framework for Component-Based Software Development: An i* Driven Approach;566
6.10.1;Introduction;566
6.10.2;Problem Statement;567
6.10.2.1;Component-Based Software Development;567
6.10.2.2;Service-Oriented Development;568
6.10.2.3;The Services Approach in Supply Chain Management;568
6.10.2.4;The Services Approach in Supply Chain Management;569
6.10.3;FaMOS-C;569
6.10.3.1;The Approach;569
6.10.3.2;Conceptual Model;570
6.10.4;Case Study;571
6.10.4.1;Outbound Logistics;571
6.10.4.2;Third Party Components;572
6.10.4.3;Framework Application;573
6.10.4.4;Component Selection;574
6.10.5;Related Work;575
6.10.6;Conclusions;576
6.10.7;References;577
6.11;A Process for Developing Adaptable and Open Service Systems: Application in Supply Chain Management;579
6.11.1;Introduction;579
6.11.2;Research Approach and Contributions;580
6.11.2.1;ProDAOSS: A Methodology for Developing Service-OrientedMAS;580
6.11.2.2;Actor Collaboration in Supply Chain Management;581
6.11.2.3;The Services Approach in Supply Chain Management;582
6.11.2.4;MAS in Supply Chain Management: A Service-Center Approach;582
6.11.3;Outbound Logistics;583
6.11.4;The Outbound Logistics Software Development: ProDAOSS Approach;583
6.11.4.1;Application Analysis;584
6.11.4.2;Application Design;586
6.11.5;Related Work;588
6.11.6;Conclusions;589
6.11.7;References;590
6.12;Business Process-Awareness in the Maintenance Activities;592
6.12.1;Introduction;592
6.12.2;Business Knowledge in Software Maintenance;593
6.12.3;Design of the Study;595
6.12.4;Results;598
6.12.5;Related Work;601
6.12.6;Threats to Validity;602
6.12.7;Conclusions and Future Work;603
6.12.8;References;603
6.13;BORM-points: Introduction and Results of Practical Testing;605
6.13.1;Introduction;605
6.13.2;The BORM-Points Method;606
6.13.2.1;Complexity Estimation Using BORMp;606
6.13.2.2;The Unadjusted Part of BORMp;606
6.13.2.3;Adjusted BORMp Part;609
6.13.2.4;The Productivity Factor;612
6.13.3;Total BORMp;612
6.13.4;BORMpTesting;612
6.13.4.1;Projects Description and Testing Procedure;613
6.13.4.2;Results;613
6.13.5;Conclusions;613
6.13.6;References;614
6.14;A Technology Classification Model for Mobile Content and Service Delivery Platforms;615
6.14.1;Introduction;615
6.14.2;Methodology;617
6.14.3;The CSDP Technology Classification Model;618
6.14.3.1;The CSDP Functional Architecture;618
6.14.3.2;The Identification of the Model’s Technology Classification Variables;620
6.14.4;The Model Application to the Companies Sample;622
6.14.4.1;The CSDP Categories;622
6.14.4.2;The CSDP Classification Matrices;623
6.14.4.3;The Offer State of the Art;626
6.14.5;Conclusions;626
6.14.6;References;627
6.15;Patterns for Modeling and Composing Workflows from Grid Services;630
6.15.1;Introduction;630
6.15.1.1;Motivation;630
6.15.1.2;Our Contribution;631
6.15.1.3;Paper Reminder;632
6.15.2;Related Works;632
6.15.3;UML Profile for Systematic Grid Services Composition;633
6.15.4;Grid Services Workflows Composition Patterns;634
6.15.4.1;Formalization;634
6.15.4.2;Sequence Pattern;636
6.15.4.3;And-branches Pattern;636
6.15.4.4;Alternative Branches Pattern;637
6.15.4.5;Loop Pattern;637
6.15.4.6;Alternative Services Pattern;637
6.15.5;Illustration of the Composition ofWorkflows from Grid Services;638
6.15.6;Conclusions;640
6.15.7;References;640
6.16;A Case Study of Knowledge Management Usage in Agile Software Projects;642
6.16.1;Introduction;642
6.16.2;Background;643
6.16.3;Case Study;644
6.16.3.1;Context;644
6.16.3.2;Research Instruments;645
6.16.3.3;Data Analysis;646
6.16.4;Discussions and Lessons Learned;648
6.16.5;Related Work;650
6.16.6;Conclusions;651
6.16.7;References;652
6.17;A Hierarchical Product-Property Model to Support Product Classification and Manage Structural and Planning Data;654
6.17.1;Introduction;654
6.17.2;Proposed Approach;655
6.17.2.1;Product Classification;655
6.17.2.2;Product Unambiguous Definition;657
6.17.2.3;Product Structure;659
6.17.3;Case Study;662
6.17.4;Final Remarks;665
6.17.5;References;665
6.18;Collaborative, Participative and Interactive Enterprise Modeling;666
6.18.1;Introduction;666
6.18.2;Collaborative-Participative-Interactive Enterprise Modeling;667
6.18.2.1;Collaboration;668
6.18.2.2;Participation;668
6.18.2.3;Interaction;668
6.18.3;The Modeling Method Consideration;669
6.18.4;DEMO Transaction;670
6.18.4.1;Original Notations;670
6.18.4.2;Extended Notations;671
6.18.5;Case Study: DutchPlast BV Enterprise;672
6.18.5.1;CPI Enterprise Modeling;673
6.18.5.2;The Customer Order Process;673
6.18.5.3;DutchPlast Business Transactions;675
6.18.6;Conclusions;675
6.18.7;References;676
7;Part IV Software Agents and Internet Computing;678
7.1;e-Learning in Logistics Cost Accounting Automatic Generation and Marking of Exercises;679
7.1.1;Denotation;679
7.1.2;Logistics Cost Accounting;680
7.1.3;Logistics Cost Accounting in e-Learning;681
7.1.4;E-Learning Concept;683
7.1.4.1;Overview;683
7.1.4.2;Generation of Exercises;683
7.1.4.3;Difficulty Levels;685
7.1.4.4;Practising with Exercises;685
7.1.4.5;Automatic Marking;685
7.1.5;System Architecture;687
7.1.6;Conclusions;688
7.1.7;References;689
7.2;Towards Successful Virtual Communities;691
7.2.1;Introduction;691
7.2.2;Business Dimension;692
7.2.2.1;Startup Cost;692
7.2.2.2;The Media Factor;692
7.2.2.3;Only Actor or First Mover in the Market;693
7.2.2.4;Attracting Users and Developing Loyalty;693
7.2.2.5;Monetizing the Community;694
7.2.3;Technical Dimension;695
7.2.3.1;Centralization vs. Decentralization;695
7.2.3.2;Incremental Deployment;695
7.2.3.3;Downtime, Availability, Performance;696
7.2.3.4;Context Awareness;696
7.2.3.5;Integrating User Experience;697
7.2.4;Social Dimension;697
7.2.4.1;Profiles Management;697
7.2.4.2;Privacy and Anonymity;698
7.2.4.3;Acceptance;698
7.2.5;Conclusions;700
7.2.6;References;700
7.3;A Multiagent-System for Automated Resource Allocation in the IT Infrastructure of a Medium-Sized Internet Service Provider;703
7.3.1;Introduction;703
7.3.2;Automated Economic Resource Allocation;704
7.3.3;Web Hosting System for a Medium-Sized ISP;705
7.3.4;Agent-Based Resource Allocation Model;705
7.3.4.1;Multi-agent Model;705
7.3.4.2;Formal Model Description;708
7.3.5;Simulation Experiments;713
7.3.6;Conclusions;716
7.3.7;References;717
7.4;AgEx: A Financial Market Simulation Tool for Software Agents;718
7.4.1;Introduction;718
7.4.2;AgEx Architecture;719
7.4.2.1;Main Components;719
7.4.2.2;Communication and AgEx Ontology;720
7.4.2.3;Simulation Mechanism;721
7.4.2.4;Real Operation Mechanism;721
7.4.3;AgEx Implementation;722
7.4.3.1;Simulation Generated Data;723
7.4.3.2;Importing Data;723
7.4.4;Related Work;723
7.4.5;AgEx in Action;724
7.4.5.1;Experimental Setup;724
7.4.5.2;Risk and Return Performance;725
7.4.5.3;Broker’s Fee Influence;726
7.4.5.4;Trader Performance by Paper;727
7.4.6;Conclusions;728
7.4.7;References;728
7.5;A Domain Analysis Approach for Multi-agent Systems Product Lines;730
7.5.1;Introduction;730
7.5.2;An Overview of Existing SPL and MAS Approaches;731
7.5.3;OLIS Case Study;732
7.5.4;Modeling OLIS in Domain Analysis with a PASSI Extension;734
7.5.4.1;Feature Modeling;735
7.5.4.2;Domain Requirements Description;735
7.5.4.3;Agent Identification;736
7.5.4.4;Role Identification;736
7.5.4.5;Task Specification;737
7.5.4.6;PASSI Adaptations - Overview;737
7.5.5;Discussions;738
7.5.6;Conclusions and Future Work;739
7.5.7;References;740
7.6;A Reputation-Based Game for Tasks Allocation;742
7.6.1;Introduction;742
7.6.2;Preliminaries on Mechanism Design;743
7.6.3;Tasks Allocation Problems;744
7.6.4;Reputation-Based Tasks Allocation Problem;745
7.6.5;Experiment;746
7.6.6;Conclusions;749
7.6.7;References;749
7.7;Remote Controlling and Monitoring of Safety Devices Using Web-Interface Embedded Systems;751
7.7.1;Introduction;751
7.7.2;Key Features of the System;752
7.7.2.1;Compatibility;752
7.7.2.2;Monolithic Structure;752
7.7.2.3;Security;753
7.7.2.4;Ease in Management and Maintenance;753
7.7.3;System Design;754
7.7.3.1;Operating System;754
7.7.3.2;Software Components Design;755
7.7.3.3;Real-Life Application: “Indalo”, a “Premier” Alarm Panel Controller;755
7.7.4;Conclusions;757
7.7.5;References;758
7.8;Recognizing Customers’ Mood in 3D Shopping Malls Based on the Trajectories of Their Avatars;759
7.8.1;Introduction;759
7.8.2;Assessing Cognitive State;760
7.8.2.1;The Poster Shop Scenario;761
7.8.3;Distributed User Modelling;762
7.8.4;Trajectory Comparison;764
7.8.4.1;Levenshtein Distance;764
7.8.5;Experiments;765
7.8.5.1;Design of Experiments;766
7.8.5.2;Discussion of Results;768
7.8.6;Conclusions;770
7.8.7;References;770
7.9;Assembling and Managing Virtual Organizations out of Multi-party Contracts;772
7.9.1;Introduction;772
7.9.2;The Running Example;773
7.9.3;The SPICA Negotiation Protocol;774
7.9.3.1;Contract Templates and Contracts;774
7.9.3.2;The Protocol;775
7.9.3.3;Individual Marketplaces;776
7.9.3.4;Putting Marketplaces Together;778
7.9.4;Implementation in Brief;778
7.9.5;Discussion;779
7.9.6;Related Work;781
7.9.7;Conclusions;782
7.9.8;References;782
7.10;A Video-Based Biometric Authentication for e-Learning Web Applications;784
7.10.1;Introduction;784
7.10.2;Biometrics;785
7.10.2.1;Face Recognition;785
7.10.3;Proposed System;786
7.10.3.1;Face Detection;786
7.10.3.2;Feature Extraction and Face Recognition;787
7.10.3.3;System Architecture;787
7.10.4;Experiments;789
7.10.5;Experimental Results;789
7.10.6;Conclusions;792
7.10.7;References;792
7.11;Modeling JADE Agents from GAIA Methodology under the Perspective of Semantic Web;794
7.11.1;Introduction;794
7.11.2;Ontologies;795
7.11.2.1;JADE Ontology;797
7.11.2.2;GAIA-JADE Mapping;799
7.11.3;Case Study;799
7.11.4;Related Works;801
7.11.4.1;Discussion;802
7.11.5;Conclusions;802
7.11.6;Additional Authors;803
7.11.7;References;803
7.12;A Business Service Selection Model for Automated Web Service Discovery Requirements;804
7.12.1;Introduction;804
7.12.1.1;Automated Web Service Discovery;805
7.12.1.2;Technical WS Discovery Solutions;805
7.12.1.3;Using a Business Service Metaphor;806
7.12.2;Current WS Discovery Solutions;806
7.12.2.1;UDDI Enhancements;806
7.12.2.2;Other Solutions;807
7.12.2.3;Distributed or Centralized Discovery Solutions;807
7.12.2.4;Semantic Concerns;808
7.12.3;A Business Model for Web Service Discovery;808
7.12.3.1;Generic Service Discovery/Selection;809
7.12.3.2;Software Service Discovery;809
7.12.4;The Business of WS Discovery Requirements;810
7.12.4.1;General Requirements;810
7.12.4.2;Semantic Information;811
7.12.4.3;Adapters;811
7.12.4.4;Standards Compliance;812
7.12.4.5;Security;813
7.12.4.6;Business Environment Change;813
7.12.4.7;The Issue of State;814
7.12.4.8;Metadata;814
7.12.5;Conclusions;815
7.12.6;References;816
8;Part V Human-Computer Interaction;818
8.1;An Agile Process Model for Inclusive Software Development;819
8.1.1;Introduction;819
8.1.2;Background;820
8.1.2.1;The Agile Methods;820
8.1.2.2;Human-Computer Interaction and Participatory Design;822
8.1.2.3;Participatory Practices Based on Organizational Semiotics;823
8.1.3;Delineating a Development Process;824
8.1.4;The Agile Inclusive Process Model;825
8.1.5;The AIPM in Practice;828
8.1.6;Conclusions;829
8.1.7;References;829
8.2;Creation and Maintenance of Query Expansion Rules;831
8.2.1;Introduction;831
8.2.2;Related Work;832
8.2.3;Semi-automatic Thesaurus Creation and Maintenance;833
8.2.3.1;Architecture;835
8.2.3.2;Detection of Candidates for Synonymy;836
8.2.3.3;Interactive Definition of Synonymy Rule;836
8.2.4;Experiment;839
8.2.5;Conclusions;840
8.2.6;References;841
8.3;Stories and Scenarios Working with Culture-Art and Design in a Cross-Cultural Context;843
8.3.1;Introduction;843
8.3.2;Scenarios and Stories in the Interaction Design and Communication Process;844
8.3.3;Research Factors;845
8.3.4;Experiment 1;846
8.3.4.1;Method and Participants;846
8.3.4.2;Scenarios and Stories in Experience Prototyping;846
8.3.4.3;Scenarios in Interaction Design;848
8.3.5;Experiment 2;848
8.3.6;Results;849
8.3.6.1;The Impact of Real Stories on the Creation of Interaction Scenarios;849
8.3.6.2;The Impact of the Theatre Technique as a Resource to Communicate Objectively the Purposes of Interaction Scenarios;850
8.3.7;Discussion and Future Works;851
8.3.7.1;Technological Insights from Stories;851
8.3.7.2;Storyboards and Theatre as Complementary Strategies;851
8.3.7.3;Vote of Trust;852
8.3.8;Conclusions;852
8.3.9;References;853
8.4;End-User Development for Individualized Information Management: Analysis of Problem Domains and Solution Approaches;855
8.4.1;Introduction;855
8.4.2;Background and Setup;857
8.4.2.1;Theories of Technology Acceptance;857
8.4.2.2;Preliminary Studies;857
8.4.2.3;Setup of Questionnaire;858
8.4.3;Results;858
8.4.3.1;Users and Software;858
8.4.3.2;Accessing Enterprise Data;861
8.4.3.3;EUD for Information Access;862
8.4.3.4;Post-Processing Enterprise Data;864
8.4.3.5;EUD of Enterprise Queries;866
8.4.4;Summary and Outlook;867
8.4.5;References;868
8.5;Evaluating the Accessibility of Websites to Define Indicators in Service Level Agreements;870
8.5.1;Introduction;870
8.5.2;WEB Accessibility;871
8.5.3;Service Level Agreement;871
8.5.4;Approach to Defining SLA Accessibility Indicators;872
8.5.5;Application;873
8.5.6;Related Work;879
8.5.7;Conclusions;880
8.5.8;References;880
8.6;Promoting Collaboration through a Culturally Contextualized Narrative Game;882
8.6.1;Introduction;882
8.6.2;Narrative Games;884
8.6.2.1;Contexteller;884
8.6.3;Conclusions;892
8.6.4;References;892
8.7;Applying the Discourse Theory to the Moderator’s Interferences in Web Debates;894
8.7.1;Introduction;894
8.7.2;Discourse Theory and the Role of the Moderator;895
8.7.3;Government-Citizen Interactive Model;897
8.7.3.1;Moderator’s Interference;899
8.7.4;Democratic Citizenship Community;900
8.7.5;Case Study;901
8.7.5.1;Methodology;901
8.7.5.2;Data Analysis;902
8.7.6;Conclusions;904
8.7.7;References;905
8.8;ExpertKanseiWeb: A Tool to Design Kansei Website;906
8.8.1;Introduction;906
8.8.2;Emotional Design of e-Commerce Websites;907
8.8.3;Kansei Engineering;907
8.8.4;Research Method;908
8.8.5;Phase I: Kansei Measurement;908
8.8.5.1;Research Instruments;908
8.8.5.2;Participants;909
8.8.5.3;Procedure;909
8.8.6;Phase II: Guideline Development;909
8.8.6.1;Partial Least Square (PLS) Analysis;910
8.8.7;Phase III: Design Tool Development;912
8.8.7.1;Kansei Web Database System (KWDS);912
8.8.7.2;The Client Interface (CI);913
8.8.8;Conclusions;915
8.8.9;References;916
8.9;Evaluation of Information Systems Supporting Asset Lifecycle Management;918
8.9.1;Introduction;918
8.9.2;Asset Management;919
8.9.3;IS for Asset Management;920
8.9.4;Issues with Evaluation of IS for Asset Management;920
8.9.4.1;Conceptual Limitations of IS Evaluation;921
8.9.4.2;Operational Limitations of IS Evaluation;922
8.9.5;IS for Asset Management Evaluation;923
8.9.6;IS for Asset Management Evaluation;927
8.9.7;References;928
8.10;Fast Unsupervised Classification for Handwritten Stroke Analysis;930
8.10.1;Introduction;930
8.10.2;Related Work;931
8.10.3;Method;932
8.10.3.1;Level 1: Feature Extraction;933
8.10.3.2;Level 2: Simplified ART2;933
8.10.3.3;Refinement;934
8.10.4;Results;934
8.10.5;Conclusions;938
8.10.6;References;939
8.11;Interfaces for All: A Tailoring-Based Approach;940
8.11.1;Introduction;940
8.11.2;Background Work and Theoretical Reference;941
8.11.2.1;Organizational Semiotics;942
8.11.3;Building a Tailorable Application;942
8.11.3.1;Gathering Requirements from the Diversity;943
8.11.3.2;Designing a Universal Solution;946
8.11.3.3;Building and Evaluating the Solution;947
8.11.4;Discussion and Lessons Learned;948
8.11.5;Conclusions;949
8.11.6;References;950
8.12;Integrating Google Earth within OLAP Tools for Multidimensional Exploration and Analysis of Spatial Data;952
8.12.1;Introduction;952
8.12.2;Related Work on SOLAP;954
8.12.3;The GooLAP System;956
8.12.4;Architecture;960
8.12.5;Conclusions and Future Work;962
8.12.6;References;962
8.13;An Automated Meeting Assistant: A Tangible Mixed Reality Interface for the AMIDA Automatic Content Linking Device;964
8.13.1;Introduction;964
8.13.2;Previous and Related Work;965
8.13.3;Setup;967
8.13.4;System Architecture;967
8.13.4.1;Smart Projector;968
8.13.4.2;ProjectionManager;968
8.13.4.3;Display Applications;968
8.13.4.4;Hub Interface;969
8.13.5;User Interface;969
8.13.5.1;Document Handling;970
8.13.5.2;Keyboard Forwarding;970
8.13.5.3;Sharing;970
8.13.5.4;Auto-arrangement and Auto-iconizing;971
8.13.6;Results;972
8.13.7;Future Work;973
8.13.8;References;974
8.14;Investigation of Error in 2D Vibrotactile Position Cues with Respect to Visual and Haptic Display Properties: A Radial Expansion Model for Improved Cuing;975
8.14.1;Introduction;975
8.14.2;Experimental Methods;977
8.14.2.1;Participants;977
8.14.2.2;Materials;977
8.14.2.3;Design;978
8.14.2.4;Procedure;979
8.14.3;Results and Discussion;980
8.14.3.1;Error Magnitude Metric;980
8.14.3.2;Radial ErrorMetric;982
8.14.4;Conclusions;984
8.14.5;References;985
8.15;Developing a Model to Measure User Satisfaction and Success of Virtual Meeting Tools in an Organization;987
8.15.1;Introduction;987
8.15.2;Virtual Meeting Tools in General;988
8.15.2.1;What Is a VMT and What Are the Offerings of a VMT;988
8.15.2.2;Problems with the VMT;988
8.15.3;The Case Organization and VMT System;989
8.15.4;User Satisfaction in IS Evaluation;991
8.15.4.1;User Satisfaction as an Evaluation Construct;991
8.15.4.2;User Satisfaction Measuring Models;992
8.15.5;Research Methodology;992
8.15.5.1;Study Design;992
8.15.5.2;Instrumentation;993
8.15.6;Data Analysis;994
8.15.6.1;Factor Analysis;994
8.15.6.2;Reliability and Item-to-Total Correlation;995
8.15.6.3;Construct Validity;996
8.15.6.4;Criterion-Related Validity;996
8.15.7;The Proposed Model and Some Discussion;997
8.15.8;Conclusions and Future Research;998
8.15.9;References;998
9;Author Index;1000
