Experience Management : Foundations, Development Methodology, and Internet-Based Applications

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Experience Management : Foundations, Development Methodology, and Internet-Based Applications / by Ralph Bergmann

版:

1st ed. 2002

資料種別:

電子ブック

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg, 2002

形態:

XXII, 398 p.

シリーズ名:

Lecture Notes in Artificial Intelligence ; 2432

著者名:

ISBN:

9783540457596 [3540457593]
9783662181768 [3662181762]
9783540441915 [3540441913]

書誌ID:

EB00005230

子書誌情報

フルテキスト

所蔵情報

書誌詳細

注記:

This book deals with experience management in the context of real-world applicability and realistic applications. A particular focus is given by the requirements that arise in complex problem solving and by the fact that modern experience management must be implemented as Internet-based applications. Concrete application areas that are discussed in this book are electronic commerce, diagnosis of complex technical equipment, and electronic design reuse. This book explores how experience management can be supported by information technology, especially by techniques that stem from knowledge-based systems, case-based reasoning, machine learning, and process modeling. It surveys different methods in a unified terminology and investigates them with respect to application requirements. Further, the process of application development and maintenance is highlighted, pointing out successful practically proven ways for obtaining and operating experience management applications.

主題:

Artificial Intelligence; Computer Application in Administrative Data Processing; Computer and Information Systems Applications; IT in Business; Multimedia Information Systems; e-Commerce and e-Business

言語:

英語

目次情報:

Introduction / 1：

Complex Problem Solving in the Internet Age / 1.1：

Knowledge Intensive Problem Solving / 1.1.1：

Complexity Issues / 1.1.2：

Internet-Based Applications / 1.1.3：

Example Application Scenarios / 1.2：

Electronic Commerce / 1.2.1：

Diagnosis of Complex Technical Equipment / 1.2.2：

Electronics Design / 1.2.3：

Experience Reuse / 1.3：

Basic Scenarios of Experience Reuse / 1.3.1：

Expected Benefits of Experience Reuse / 1.3.2：

Experience Management / 1.4：

Knowledge Management / 1.4.1：

Experience Management versus Knowledge Management / 1.4.2：

Experience Management Activities / 1.4.3：

Experience Management Definition / 1.4.4：

Web Technologies for Experience Management / 1.5：

Representing and Storing Experience on the Web / 1.5.1：

Accessing Experience from the Web / 1.5.2：

Limitations of Information Access Approaches for Experience Reuse / 1.5.3：

Internet Technologies as Infrastructure for Experience Management / 1.5.4：

Methods for Experience Management on the Conceptual Level / 1.6：

Overview of This Book / 1.7：

The Topic in a Nutshell / 1.7.1：

Contributions from Recent Projects / 1.7.2：

Structure of the Book / 1.7.3：

Knowledge, Experience and Their Characteristics / 2：

Data, Information, and Knowledge / 2.1.1：

Specific and General Knowledge / 2.1.2：

Experience / 2.1.3：

Representation of Experience and Related Knowledge for Reuse / 2.1.4：

General Model for Experience Management / 2.2：

Problem Solving Cycle / 2.2.1：

Development and Maintenance Methodology / 2.2.2：

Related Models / 2.3：

Knowledge Management and Organizational Memory / 2.3.1：

Quality Improvement Paradigm and Experience Factory / 2.3.2：

The Case-Based Reasoning Cycle / 2.3.3：

Knowledge Representation for Experience Management / Part I：

Representing Experience / 3：

Cases for Representing Experience / 3.1：

Basic Case Structure / 3.1.1：

A First General Formalization of Cases / 3.1.2：

Utility of Experience / 3.1.3：

Representing Experience with Respect to Utility / 3.1.4：

Overview of Case Representation Approaches / 3.2：

The Textual Approach / 3.2.1：

The Conversational Approach / 3.2.2：

The Structural Approach / 3.2.3：

Comparing the Different Approaches / 3.2.4：

Effort Required for the Different Approaches / 3.2.5：

Focus on the Structural Approach / 3.2.6：

Formalizing Structural Case Representations / 3.3：

Attribute-Value Representation / 3.3.1：

Object-Oriented Representations / 3.3.2：

Graph Representations / 3.3.3：

Predicate Logic Representations / 3.3.4：

Relation to the General Definition / 3.3.5：

Comparing Different Structural Case Representation Approaches / 3.3.6：

Generalized Cases / 3.4：

Extensional Definition of Generalized Cases / 3.4.1：

Different Kinds of Generalized Cases / 3.4.2：

Representation of Generalized Cases / 3.4.3：

Hierarchical Representations and Abstract Cases / 3.5：

Advantages of Abstract Cases / 3.5.1：

Levels of Abstraction / 3.5.2：

Kind of Cases / 3.5.3：

Languages for Structural Case Representations / 3.6：

Common Case Representation Language CASUEL / 3.6.1：

The XML-based Orenge Modeling Language OML / 3.6.2：

Choice of the Vocabulary / 3.7：

Characterization Part / 3.7.1：

Lesson Part / 3.7.2：

Choice of Types / 3.7.3：

Assessing Experience Utility / 4：

Approximating Utility with Similarity / 4.1：

Traditional View of Case-Based Reasoning / 4.1.1：

Extended View / 4.1.2：

Similarity Measures / 4.1.3：

Relations between Similarity and Utility / 4.1.4：

General Considerations Concerning Similarity and Distance / 4.2：

Distance Measures / 4.2.1：

Possible Properties of Similarity Measures / 4.2.2：

Similarity and Fuzzy Sets / 4.2.3：

Similarity Measures for Attribute-Value Representations / 4.3：

Simple Measures for Binary Attributes / 4.3.1：

Simple Measures for Numerical Attributes / 4.3.2：

TheLocal-Global Principle / 4.3.3：

Local Similarity Measures for Numeric Attributes / 4.3.4：

Local Similarity Measures for Unordered and Totally Ordered Symbolic Attributes / 4.3.5：

Taxonomically Ordered Symbolic Types / 4.3.6：

Global Similarity Measures / 4.3.7：

Similarity Measures for Object-Oriented Representations / 4.4：

Example Use of Class Hierarchies and Object Similarities / 4.4.1：

Computing Object Similarities / 4.4.2：

Handling Multi-value Attributes / 4.4.3：

Related Approaches / 4.4.4：

Similarity Measures for Graph Representations / 4.5：

Graph Matching / 4.5.1：

Graph Editing / 4.5.2：

Similarity Measures for Predicate Logic Representations / 4.6：

Treating Atomic Formulas as Binary Attributes / 4.6.1：

Similarity between Atomic Formulas / 4.6.2：

Similarity through Logical Inference / 4.6.3：

Similarity for Generalized Cases / 4.7：

Canonical Extension of a Similarity Measure / 4.7.1：

The General Problem of Similarity Assessment / 4.7.2：

Representing Knowledge for Adaptation / 5：

Rule-Based Representations / 5.1：

Different Kinds of Rules / 5.1.1：

Formalization for Rules in an Object-Oriented Framework / 5.1.2：

An Example / 5.1.3：

Operator-Based Representations / 5.2：

Basic Approach / 5.2.1：

Representation / 5.2.2：

Restricting Adaptability with Consistency Constraints / 5.3：

Methods for Experience Management / 5.4：

User Communication / 6：

Introduction to User Interaction / 6.1：

A Basic Communication Architecture / 6.1.1：

Requirements / 6.1.2：

Distribution between Client and Server Side / 6.1.3：

A Formal Dialog Model / 6.2：

Overview / 6.2.1：

Dialog Situation / 6.2.2：

Dialog Interactions / 6.2.3：

Dialog Strategy and Its Execution / 6.2.4：

Predefined Static Dialog / 6.3：

Three-Step Questionnaire-Based Problem Acquisition / 6.3.1：

Static Domain Specific Dialogs / 6.3.2：

Dynamic and Adaptable Strategies / 6.4：

Criteria for Attribute Selection / 6.4.1：

Compiling Dialog Strategies / 6.4.2：

Dynamically Interpreted Strategies / 6.4.3：

Learning from User Interaction / 6.4.4：

Experience Presentation / 6.5：

Simple Lesson Lists / 6.5.1：

Experience Lists with External Links / 6.5.2：

Adding Similarity Explanations / 6.5.3：

Adaptive Experience Presentation / 6.5.4：

Experience Retrieval / 7：

General Considerations / 7.1：

Formal Retrieval Task / 7.1.1：

Storing Case Data in Databases / 7.1.2：

Overview of Approaches / 7.1.3：

Sequential Retrieval / 7.2：

Indexing by kd-Tree Variants / 7.3：

The Standard kd-Tree / 7.3.1：

The Inreca Tree / 7.3.2：

Building the Inreca Tree / 7.3.3：

Retrieval with the Inreca-Tree / 7.3.4：

Properties of kd-Tree Based Retrieval / 7.3.5：

Fish and Shrink Retrieval / 7.4：

BasicIdea / 7.4.1：

Retrieval Algorithm / 7.4.2：

Properties ofFish and Shrink / 7.4.3：

Case Retrieval Nets / 7.5：

The Case Retrieval Net Index Structure / 7.5.1：

The Retrieval Algorithm / 7.5.2：

Properties of Case Retrieval Nets / 7.5.3：

SQL Approximation / 7.6：

The Basic Idea / 7.6.1：

Properties of SQL Approximation / 7.6.2：

Summary / 7.7：

Experience Adaptation / 8：

Overview and Characterization of Different Adaptation Approaches / 8.1：

The Continuum of Adaptation Models / 8.1.1：

Generative Adaptation / 8.1.2：

Compositional Adaptation / 8.1.3：

Hierarchical Adaptation / 8.1.4：

Adaptation for Experience Management for Complex Problem Solving / 8.1.5：

Theory of Transformational Adaptation / 8.2：

Experience Transformations / 8.2.1：

The Experience Transformation Process / 8.2.2：

Similarity Measures in the Context of Experience Transformations / 8.2.3：

Relation to Rewrite Systems / 8.2.4：

Relation to Generalized Cases / 8.2.5：

Adaptation with Explicit Transformation Knowledge / 8.3：

Rule-Based Adaptation / 8.3.1：

Interactive Operator-Based Adaptation / 8.3.2：

Incremental Compositional Adaptation / 8.4：

Highly Structured Problems / 8.4.1：

Compositional Approach / 8.4.2：

The Adaptation Cycle / 8.4.3：

Controlling the Adaptation Cycle / 8.4.4：

Adaptation as Hill-Climbing Search / 8.4.5：

Developing and Maintaining Experience Management Applications / 9：

General Purpose of a Methodology / 9.1：

Methodology for Experience Management / 9.1.2：

Contributions to Methodology Development / 9.1.3：

INRECA Methodology Overview / 9.2：

Process Modeling / 9.2.1：

Experience Captured in Software Process Models / 9.2.2：

The INRECA Experience Base / 9.3：

Process Modeling in INRECA / 9.4：

Technical, Organizational, and Managerial Processes / 9.4.1：

Interaction among Processes / 9.4.2：

Combining Processes to Process Models / 9.4.3：

Generic and Specific Descriptions / 9.4.4：

The Common Generic Level / 9.5：

Managerial Processes / 9.5.1：

Technical Processes: Software Development / 9.5.3：

Organizational Processes / 9.5.4：

Documenting the INRECA Experience / 9.6：

Process Description Sheets / 9.6.1：

Product Description Sheets / 9.6.2：

Simple Method Description Sheets / 9.6.3：

Complex Method Description Sheets / 9.6.4：

Reusing and Maintaining INRECA Experience / 9.7：

The INRECA Reuse Procedure / 9.7.1：

Relations to the EMM Problem Solving Cycle / 9.7.2：

Development and Maintenance of the INRECA Experience Base / 9.7.3：

Tool Support for the INRECA Methodology / 9.8：

INRECA Experience Modeling Methodology Tool / 9.8.1：

Knowledge Modeling Tools / 9.8.2：

Experience Management Application Areas / Part III：

Experience Management for Electronic Commerce / 10：

Introduction to the Electronic Commerce Scenario / 10.1：

Electronic Commerce Definition / 10.1.1：

Transaction Model / 10.1.2：

Knowledge Involved in Electronic Commerce / 10.1.3：

Opportunities for Experience Management Support / 10.1.4：

Analyzing Pre-sales Scenarios / 10.2：

Customer Wishes / 10.2.1：

Products / 10.2.2：

Experience Representation for Product Search / 10.2.3：

WEBSELL: A Generic Electronic Commerce Architecture / 10.3：

Pathways Server and Dialog Components / 10.3.1：

Case-Based Retrieval / 10.3.2：

Collaborative Recommendation / 10.3.3：

Customization / 10.3.4：

Methodology Recipe for Electronic Commerce / 10.4：

Requirements Acquisition / 10.4.1：

Knowledge Modeling / 10.4.2：

GUI Development / 10.4.3：

Implement CBR Retrieval Engine / 10.4.4：

Integrate CBR and GUI / 10.4.5：

Application Overview / 10.5：

Application: Product Catalog for Operational Amplifiers / 10.6：

Vocabulary and User Interface / 10.6.1：

Benefit Analysis / 10.6.2：

Application: Customization of Electro-mechanical Components / 10.7：

Vocabulary, Retrieval, Customization, and User Interface / 10.7.1：

Experience Management for Self-Service and Help-Desk Support / 10.7.2：

Structure and Representation of the Experience Base / 11.1：

Object-Oriented Representation / 11.2.1：

Case Structure / 11.2.2：

Partitioning the Experience Base / 11.2.3：

User and Roles / 11.3：

Overall Architecture / 11.4：

The Server / 11.4.1：

The HOMER Client / 11.4.2：

Hotline Component / 11.5：

Create a New Problem Description / 11.5.1：

Retrieving Problem Solutions / 11.5.2：

Feedback from Problem Solving / 11.5.3：

Methodology Recipe for Help-Desk Applications / 11.6：

Managerial Processes during System Development / 11.6.1：

Organizational Processes during System Development / 11.6.2：

Technical Processes during System Development / 11.6.3：

Managerial Processes during System Use / 11.6.4：

Organizational Processes during System Use / 11.6.5：

Technical Processes during System Use / 11.6.6：

Process Model for a Help-Desk Project / 11.6.7：

Evaluation of HOMER / 11.7：

Benefits for the Help-Desk Operators / 11.7.1：

Evaluation of the Methodology Recipe / 11.7.2：

Experience Management for Electronic Design Reuse / 11.8：

Electronic Design Reuse / 12.1：

Intellectual Properties / 12.1.1：

IP Reuse / 12.1.2：

Existing IP Reuse Support / 12.1.3：

Challenges of Experience Management for IP Reuse / 12.1.4：

Representation of Intellectual Properties / 12.2：

IP Taxonomy / 12.2.1：

IP Attributes / 12.2.2：

IP Representation as Generalized Cases / 12.2.3：

An Example IP / 12.2.4：

Descriptions of Design Problems and Reuse-Related Knowledge / 12.3：

Problem Descriptions / 12.3.1：

The READEE Prototype for DSP Selection / 12.3.2：

Issues ofFuture Research / 12.5：

List of Symbols

References

Index

Introduction / 1：

Complex Problem Solving in the Internet Age / 1.1：

Knowledge Intensive Problem Solving / 1.1.1：

Complexity Issues / 1.1.2：

Internet-Based Applications / 1.1.3：

Example Application Scenarios / 1.2：

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