Yao Web-based Support Systems

1. Auflage 2010
ISBN: 978-1-84882-628-1
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 440 Seiten

Web-based Support Systems (WSS) are an emerging multidisciplinary research area in which one studies the support of human activities with the Web as the common platform,mediumandinterface.TheInternetaffectseveryaspectofourmodernlife. Moving support systems to online is an increasing trend in many research domains. One of the goals of WSS research is to extend the human physical limitation of information processing in the information age. Research on WSS is motivated by the challenges and opportunities arising from the Internet. The availability, accessibility and ?exibility of information as well as the tools to access this information lead to a vast amount of opportunities. H- ever, there are also many challenges we face. For instance, we have to deal with more complex tasks, as there are increasing demands for quality and productivity. WSS research is a natural evolution of the studies on various computerized support systems such as Decision Support Systems (DSS), Computer Aided Design (CAD), and Computer Aided Software Engineering (CASE). The recent advancement of computer and Web technologies make the implementation of more feasible WSS. Nowadays, it is rare to see a system without some type of Web interaction. The research of WSS is classi?ed into four groups. • WSS for speci?c domains.

Autoren/Hrsg.

Yao, JingTao

Inhaltsverzeichnis

1;Preface;5
2;Contents;9
3;List of Contributors;18
4;Part I Web-Based Support Systems for Specific Domains;22
4.1;1 Context-Aware Adaptation in Web-Based Groupware Systems;23
4.1.1;1.1 Introduction;24
4.1.1.1;1.1.1 The Web and the Collaboration Issue in Mobile Environment;24
4.1.1.2;1.1.2 Adaptation to Web-Based Groupware SystemsMobile Users;25
4.1.1.3;1.1.3 A Context- and Preference-Based Adaptationfor Web-Based Groupware Systems;26
4.1.1.4;1.1.4 Chapter Organization;27
4.1.2;1.2 Related Work;27
4.1.3;1.3 Context Representation;29
4.1.4;1.4 Representation of the Group Awareness Information;32
4.1.5;1.5 Representing User's Preferences;33
4.1.5.1;1.5.1 Filtering Rules;34
4.1.5.2;1.5.2 Context-Aware Profiles;36
4.1.5.3;1.5.3 Contextual Conditions;37
4.1.5.4;1.5.4 Personalizing Informational Content;38
4.1.5.5;1.5.5 Sharing Profiles;40
4.1.6;1.6 Filtering Process;41
4.1.6.1;1.6.1 Selecting Profiles;41
4.1.6.2;1.6.2 Selecting and Organizing Content;43
4.1.7;1.7 Implementation;46
4.1.7.1;1.7.1 BW-M Framework;46
4.1.7.2;1.7.2 Implementation Issues;47
4.1.8;1.8 Conclusion;48
4.1.9;References;49
4.2;2 Framework for Supporting Web-Based Collaborative Applications;52
4.2.1;2.1 Introduction;52
4.2.1.1;2.1.1 Barriers and Obstacles;53
4.2.1.2;2.1.2 Research Motivations;53
4.2.1.3;2.1.3 Benefits;54
4.2.1.4;2.1.4 Research Questions and Aims;54
4.2.2;2.2 Research Background;54
4.2.2.1;2.2.1 Service System;54
4.2.2.2;2.2.2 Dynamic Re-configurable System;55
4.2.3;2.3 Solution Approach;56
4.2.3.1;2.3.1 Dynamic Services Management;56
4.2.3.2;2.3.2 Service Availability;57
4.2.3.3;2.3.3 Services Invocation and Execution;57
4.2.4;2.4 Application – Web-based Solution for e-Health;58
4.2.5;2.5 Conclusion ;60
4.2.6;References;60
4.3;3 Helplets: A Common Sense-Based Collaborative Help Collection and Retrieval Architecture for Web-Enabled Systems;62
4.3.1;3.1 Introduction;63
4.3.2;3.2 Issues in Contemporary Help Systems;64
4.3.2.1;3.2.1 Tutorial Embedding;65
4.3.2.2;3.2.2 Tutorial Decomposition;65
4.3.3;3.3 Machine Common Sense;65
4.3.4;3.4 Helplet Architecture;67
4.3.4.1;3.4.1 Knowlege Collection: Helplets;69
4.3.4.2;3.4.2 Knowledge Organization: Folksonomy;69
4.3.4.3;3.4.3 Knowledge Retrieval: Common Sense;71
4.3.4.3.1;3.4.3.1 Machine Common Sense and Helplets;72
4.3.4.3.2;3.4.3.2 Central Problems of Folksonomy;72
4.3.4.3.3;3.4.3.3 Flow of Control;72
4.3.4.3.4;3.4.3.4 User Preferences;73
4.3.4.3.5;3.4.3.5 Score Vector;74
4.3.4.3.6;3.4.3.6 Issues in the Basic Approach;75
4.3.4.3.7;3.4.3.7 Modifications to Personalized Web Search;75
4.3.4.3.8;3.4.3.8 Enhancing the Basic Technique;76
4.3.5;3.5 Related Work;79
4.3.6;3.6 Conclusion;81
4.3.7;References;82
4.4;4 Web-based Virtual Research Environments;84
4.4.1;4.1 Introduction;84
4.4.2;4.2 Short Review of VREs;86
4.4.3;4.3 Our Experience of VRE;90
4.4.3.1;4.3.1 Architecture;90
4.4.3.2;4.3.2 The Sakai Collaborative Learning Framework;91
4.4.3.3;4.3.3 Prototype: Sakai VRE Portal Demonstrator;92
4.4.3.4;4.3.4 Production: Psi-k VRE;95
4.4.3.5;4.3.5 Production: Social Science e-Infrastructure VRE;96
4.4.4;4.4 Further Discussion and Summary;97
4.4.5;References;98
4.5;5 Web-Based Learning Support System;100
4.5.1;5.1 Introduction;100
4.5.2;5.2 Learning and Learning Support Systems;101
4.5.3;5.3 Functions of Web-based Learning Support Systems;102
4.5.4;5.4 Designs and Implementation of a WLSS;104
4.5.5;5.5 The Proposed Framework Based on KSM;107
4.5.6;5.6 Rough set-based Learning Support to Predict Academic Performance;108
4.5.6.1;5.6.1 Survey and Data Collection;109
4.5.6.2;5.6.2 Results and Discussion;110
4.5.7;5.7 Conclusion;112
4.5.8;References;113
4.6;6 A Cybernetic Design Methodology for `Intelligent' Online Learning Support;115
4.6.1;6.1 Introduction;115
4.6.2;6.2 Rationale;117
4.6.3;6.3 The Need for `Intelligent' Cognition Support Systems;118
4.6.4;6.4 Metacognition as the Primary Learning Goal;121
4.6.5;6.5 A Brief History of Cognition Support Systems;124
4.6.6;6.6 Enabling Effective Cognition and Metacognition Development;128
4.6.7;6.7 Relationships and Connectedness: Pathways to Meaning;130
4.6.8;6.8 A Model for Constructing ``Intelligent'' CognitionSupport Systems;133
4.6.9;6.9 Conclusion;137
4.6.10;6.10 Research Questions for Further Study;139
4.6.11;References;140
4.7;7 A Web-Based Learning Support System for Inquiry-BasedLearning;143
4.7.1;7.1 Introduction;143
4.7.2;7.2 Web-Based Learning Support Systems and Inquiry-BasedLearning;144
4.7.2.1;7.2.1 Web-Based Learning Support Systems;144
4.7.2.2;7.2.2 Web Services;145
4.7.2.3;7.2.3 Online-Learning Games;145
4.7.2.4;7.2.4 Inquiry-Based Learning;146
4.7.2.5;7.2.5 Web-Based Learning Support Systems for Inquiry-Based Learning;147
4.7.3;7.3 Modeling Online Treasure Hunt;147
4.7.3.1;7.3.1 Treasure Hunts;147
4.7.3.2;7.3.2 Treasure Hunt Model for Inquiry-Based Learning;148
4.7.4;7.4 Implementation of Online Treasure Hunt ;150
4.7.4.1;7.4.1 Architecture of Online Treasure Hunt;150
4.7.4.2;7.4.2 Teaching Support Subsystem;151
4.7.4.3;7.4.3 Learning Support Subsystem;152
4.7.4.4;7.4.4 Treasure Hunt Game;153
4.7.4.5;7.4.5 Treasure Hunt Process;154
4.7.5;7.5 A Demonstrative Example of the System;155
4.7.6;7.6 Conclusion;159
4.7.7;References;160
5;Part II Web-Based Applications and WSS Techniques;162
5.1;8 Combinatorial Fusion Analysis for Meta Search InformationRetrieval;163
5.1.1;8.1 Introduction;163
5.1.2;8.2 Combinatorial Fusion Analysis;167
5.1.2.1;8.2.1 Multiple Scoring Systems;167
5.1.2.2;8.2.2 Rank/Score Function and the Rank-Score Characteristics (RSC) Graph;168
5.1.2.3;8.2.3 Rank and Score Combination;171
5.1.2.4;8.2.4 Performance Evaluation;172
5.1.2.5;8.2.5 Diversity;175
5.1.3;8.3 Combinatorial Fusion Analysis Applications in Information Retrieval;176
5.1.3.1;8.3.1 Predicting Fusion Results;176
5.1.3.2;8.3.2 Comparing Rank and Score Combination;177
5.1.4;8.4 Conclusion and Future Work;178
5.1.5;References;179
5.2;9 Automating Information Discovery Within the Invisible Web;182
5.2.1;9.1 Introduction;183
5.2.2;9.2 The Deep Web;184
5.2.3;9.3 State of the Art in Searching the Deep Web;187
5.2.3.1;9.3.1 Automatic Information Discovery from theInvisible Web;188
5.2.3.2;9.3.2 Query Routing: Finding Ways in the Mazeof the Deep Web;189
5.2.3.3;9.3.3 Downloading the Hidden Web Content;190
5.2.3.4;9.3.4 Information Discover, Extraction, and Integration for Hidden Web;193
5.2.4;9.4 Conclusion;195
5.2.5;References;195
5.3;10 Supporting Web Search with Visualization;197
5.3.1;10.1 Web Search and Web Support Systems;197
5.3.2;10.2 Web Information Retrieval;198
5.3.2.1;10.2.1 Traditional Information Retrieval;198
5.3.2.2;10.2.2 Information Retrieval on the Web;199
5.3.2.3;10.2.3 Web Search User Interfaces;200
5.3.2.4;10.2.4 Web Search User Behaviour;201
5.3.3;10.3 Issues in Information Visualization;202
5.3.4;10.4 A Taxonomy of Information to Support Web Search Processes;204
5.3.4.1;10.4.1 Attributes of the Query;204
5.3.4.2;10.4.2 Attributes of the Document Surrogate;205
5.3.4.3;10.4.3 Attributes of the Document;205
5.3.4.4;10.4.4 Attributes of the Search Results Set;205
5.3.4.5;10.4.5 External Knowledge Bases;206
5.3.5;10.5 Challenges in Search Representations;206
5.3.6;10.6 Seminal and State-of-the-Art Research in Visual Web Search;208
5.3.6.1;10.6.1 Query Visualization;208
5.3.6.2;10.6.2 Search Results Visualization;212
5.3.6.2.1;10.6.2.1 Document Visualization;213
5.3.6.2.2;10.6.2.2 Document Surrogate Visualization;216
5.3.6.3;10.6.3 Revisiting the Taxonomy of Information;223
5.3.7;10.7 Conclusions;224
5.3.8;References;225
5.4;11 XML Based Markup Languages for Specific Domains;229
5.4.1;11.1 Background;230
5.4.1.1;11.1.1 XML: The eXtensible Markup Language;230
5.4.1.1.1;11.1.1.1 Need for XML;230
5.4.1.1.2;11.1.1.2 XML Terminology;231
5.4.1.2;11.1.2 Domain-Specific Markup Languages;232
5.4.1.2.1;11.1.2.1 Examples of Domain-Specific Markup Languages;233
5.4.1.2.2;11.1.2.2 MatML: The Materials Markup Language;234
5.4.2;11.2 Development of Markup Languages;236
5.4.2.1;11.2.1 Acquisition of Domain Knowledge;236
5.4.2.2;11.2.2 Data Modeling;237
5.4.2.2.1;11.2.2.1 Entity Relationship Diagram;237
5.4.2.3;11.2.3 Requirements Specification;237
5.4.2.4;11.2.4 Ontology Creation;238
5.4.2.5;11.2.5 Revision of the Ontology;240
5.4.2.6;11.2.6 Schema Definition;240
5.4.2.7;11.2.7 Reiteration of the Schema;241
5.4.3;11.3 Desired Properties of Markup Languages;243
5.4.3.1;11.3.1 Avoidance of Redundancy;243
5.4.3.2;11.3.2 Non-ambiguous Presentation of Information;243
5.4.3.3;11.3.3 Easy Interpretability of Information;244
5.4.3.4;11.3.4 Incorporation of Domain-Specific Requirements;244
5.4.3.5;11.3.5 Potential for Extensibility;245
5.4.4;11.4 Application of XML Features in Language Development;245
5.4.4.1;11.4.1 Sequence Constraint;245
5.4.4.2;11.4.2 Choice Constraint;246
5.4.4.3;11.4.3 Key Constraint;246
5.4.4.4;11.4.4 Occurrence Constraint;247
5.4.5;11.5 Convenient Access to Information;249
5.4.5.1;11.5.1 XQuery: XML Query Language;249
5.4.5.2;11.5.2 XSLT: XML Style Sheet Language Transformations;250
5.4.5.3;11.5.3 XPath: XML Path Language;250
5.4.6;11.6 Conclusions;250
5.4.7;References;251
5.5;12 Evaluation, Analysis and Adaptation of Web Prefetching Techniques in Current Web;253
5.5.1;12.1 Introduction to Web Prefetching;253
5.5.1.1;12.1.1 Generic Web Architecture;254
5.5.1.2;12.1.2 Prediction Engine;255
5.5.1.3;12.1.3 Prefetching Engine;256
5.5.1.4;12.1.4 Web Prediction Algorithms;256
5.5.1.4.1;12.1.4.1 Prediction from the Access Pattern;256
5.5.1.4.2;12.1.4.2 Prediction from Web Content;257
5.5.2;12.2 Performance Evaluation;257
5.5.2.1;12.2.1 Experimental Framework;257
5.5.2.1.1;12.2.1.1 Surrogate;258
5.5.2.1.2;12.2.1.2 Client;260
5.5.2.1.3;12.2.1.3 Proxy Server;262
5.5.2.2;12.2.2 Performance Key Metrics;263
5.5.2.2.1;12.2.2.1 Prediction Related Indexes;264
5.5.2.2.2;12.2.2.2 Resource Usage Indexes;266
5.5.2.2.3;12.2.2.3 Latency Related Indexes;268
5.5.2.3;12.2.3 Comparison Methodology;268
5.5.2.4;12.2.4 Workload;270
5.5.3;12.3 Evaluation of Prefetching Algorithms;271
5.5.3.1;12.3.1 Prefetching Algorithms Description;271
5.5.3.2;12.3.2 Experimental Results;274
5.5.3.2.1;12.3.2.1 Latency Per Page Ratio;274
5.5.3.2.2;12.3.2.2 Space;275
5.5.3.2.3;12.3.2.3 Processor Time;275
5.5.3.3;12.3.3 Summary;276
5.5.4;12.4 Theoretical Limits on Performance;276
5.5.4.1;12.4.1 Metrics;276
5.5.4.2;12.4.2 Predicting at the Server;278
5.5.4.3;12.4.3 Predicting at the Client;279
5.5.4.4;12.4.4 Predicting at the Proxy;280
5.5.4.5;12.4.5 Prefetching Limits Summary;281
5.5.5;12.5 Summary and Conclusions;282
5.5.6;References;282
5.6;13 Knowledge Management System Based on Web 2.0 Technologies;286
5.6.1;13.1 Introduction;286
5.6.2;13.2 Knowledge Management Systems;287
5.6.3;13.3 Web 2.0;290
5.6.4;13.4 Rich Internet Applications Architecture;292
5.6.5;13.5 Rich Internet Application Frameworks;293
5.6.6;13.6 Developing a Knowledge-Based Management System;301
5.6.7;13.7 Implementing a Knowledge Management System;306
5.6.8;13.8 Case Study: The RV10 Project;307
5.6.9;13.9 Conclusions;312
5.6.10;References;313
6;Part III Design and Development of Web-Based Support Systems;315
6.1;14 A Web-Based System for Managing Software ArchitecturalKnowledge;316
6.1.1;14.1 Introduction;316
6.1.2;14.2 Background and Motivation;317
6.1.2.1;14.2.1 Architecture-Based Software Development;318
6.1.2.2;14.2.2 Knowledge Management Issues in Software Architecture Process;319
6.1.2.3;14.2.3 Support for Architectural Knowledge Management;320
6.1.3;14.3 Tool Support for Managing Architectural Knowledge;321
6.1.3.1;14.3.1 The Architecture of PAKME;321
6.1.3.2;14.3.2 The Data Model of PAKME;323
6.1.3.3;14.3.3 Implementation;324
6.1.4;14.4 Managing Architectural Knowledge with PAKME;326
6.1.4.1;14.4.1 Capturing and Presenting Knowledge;327
6.1.4.2;14.4.2 Supporting Knowledge Use/Reuse;330
6.1.5;14.5 An Industrial Case of Using PAKME;333
6.1.5.1;14.5.1 Use of PAKME's Knowledge Base;335
6.1.5.2;14.5.2 Use of PAKME's Project Base;335
6.1.5.3;14.5.3 Observations from the Study;336
6.1.6;14.6 Related Work;339
6.1.7;14.7 Summary;340
6.1.8;References;341
6.2;15 CoP Sensing Framework on Web-Based Environment;344
6.2.1;15.1 Introduction;344
6.2.2;15.2 Community of Practice (CoP) Characteristics;346
6.2.3;15.3 CoP Objects in the Social Learning Framework;349
6.2.4;15.4 Web-Based System for Sensing Social Learning Framework;349
6.2.4.1;15.4.1 Community Structure;351
6.2.4.1.1;15.4.1.1 Volatility of the Membership;351
6.2.4.1.2;15.4.1.2 Temporal Domination in the Community Participation Hierarchy;352
6.2.4.1.3;15.4.1.3 Existence of Common Interest;353
6.2.4.1.4;15.4.1.4 Common Interest – Activity;353
6.2.4.1.5;15.4.1.5 Common Interest – Communication;354
6.2.4.1.6;15.4.1.6 Common Interest – Relationship;355
6.2.4.1.7;15.4.1.7 Fluid Movement Between Groups;355
6.2.4.2;15.4.2 Learning Through Participation and Reification;356
6.2.4.3;15.4.3 Negotiation of Meaning;358
6.2.4.4;15.4.4 Learning as Temporal;359
6.2.4.5;15.4.5 Boundary Objects and Boundary Encounters;360
6.2.4.6;15.4.6 Mutual Engagement, Joint Enterprise, and Shared Repertoire;361
6.2.4.7;15.4.7 Identity;364
6.2.5;15.5 Integrated Schema of the Entire System;365
6.2.6;15.6 Conclusion;366
6.2.7;References;366
6.3;16 Designing a Successful Bidding Strategy Using Fuzzy Sets and Agent Attitudes;369
6.3.1;16.1 Introduction;369
6.3.2;16.2 Related Works;370
6.3.3;16.3 A Fuzzy Bidding Strategy (FA-Bid);372
6.3.3.1;16.3.1 Basic Scenario;372
6.3.3.2;16.3.2 FA-Bid Overview;373
6.3.3.3;16.3.3 Attribute Evaluation;374
6.3.3.3.1;16.3.3.1 Weights Determination;374
6.3.3.3.2;16.3.3.2 Assessment Expression;374
6.3.3.3.3;16.3.3.3 Assessments Aggregation;374
6.3.3.4;16.3.4 Attitude Estimation;376
6.3.3.5;16.3.5 Overall Assessment;376
6.3.3.6;16.3.6 Agent Price Determination;377
6.3.4;16.4 Conclusions;378
6.3.5;References;379
6.4;17 Design Scenarios for Web-Based Management of OnlineInformation;381
6.4.1;17.1 Introduction;382
6.4.2;17.2 Scenario-Based Development;383
6.4.3;17.3 Understanding Design Opportunities;385
6.4.4;17.4 Current Technologies;389
6.4.4.1;17.4.1 Input;390
6.4.4.2;17.4.2 Output;391
6.4.4.3;17.4.3 Portability;391
6.4.5;17.5 Towards New Designs;392
6.4.6;17.6 Discussion;392
6.4.7;References;395
6.5;18 Data Mining for Web-Based Support Systems: A Case Study in e-Custom Systems;397
6.5.1;18.1 Introduction;397
6.5.2;18.2 Data Mining as a Part of the Decision Making Process;399
6.5.3;18.3 Building Blocks for New Web-Based Support Systems: Web Services, SOA, Smart Seals;402
6.5.3.1;18.3.1 Web Services;402
6.5.3.2;18.3.2 Service-Oriented Architecture (SOA);403
6.5.3.3;18.3.3 Smart Seals: TREC or RFID Technology;404
6.5.4;18.4 Web-Based Support Systems for e-Business and e-Custom;405
6.5.5;18.5 Evaluation and Discussion;407
6.5.6;18.6 Conclusions;410
6.5.7;References;411
6.6;19 Service-Oriented Architecture (SOA) as a Technical Framework for Web-Based Support Systems (WSS);413
6.6.1;19.1 Introduction;413
6.6.2;19.2 Support Systems: A Historical Perspective;414
6.6.3;19.3 Service as a Medium of Information Exchange for Web-Based Support Systems;415
6.6.3.1;19.3.1 Genesis of a `Service' as Data/Input AccessCharacteristic;416
6.6.3.2;19.3.2 `Service': A Short Primer;417
6.6.3.3;19.3.3 Service-Oriented Inputs as Digestible Units for a Support System;417
6.6.3.4;19.3.4 Service-Oriented Information as Fine-GrainedOutput Decision Stream Services;418
6.6.4;19.4 Service-Oriented Architecture (SOA): An Architectural Evolution for Data Access;419
6.6.4.1;19.4.1 Service-Oriented Architecture (SOA);419
6.6.4.2;19.4.2 Rise of a Web Service: Software as a Service(SaaS) Over the Internet;421
6.6.5;19.5 SOA: The Information Gateway for Support Systems;422
6.6.5.1;19.5.1 Enterprise Service Bus: SOA's Elixir for DataAccess for Support Systems;422
6.6.5.1.1;19.5.1.1 Inside the Enterprise Service Bus;423
6.6.5.2;19.5.2 AirMod-X: A Support System Example;424
6.6.5.2.1;19.5.2.1 Challenge Scenario – 1: The Traditional Way;424
6.6.5.2.2;19.5.2.2 Challenge Scenario – 2: The SOA Way;425
6.6.5.3;19.5.3 SOA and WSS: An Interplay;426
6.6.6;19.6 Technologies for SOA Implementation for WSS;430
6.6.6.1;19.6.1 Sample WSS Scenario: AirMod-X;431
6.6.7;19.7 Conclusion;435
6.6.8;References;436
7;A Contributor's Biography;438
8;Index;447