Acquisition and understanding of process knowledge using problem solving methods / / José Manuel Gómez-Pérez

• Record Nr.: UNINA9910822426503321
• Autore: Gómez-Pérez José Manuel
• Pubbl/distr/stampa: Heidelberg, Germany : , : IOS Press : , : AKA, , 2010; ©2010
• ISBN: 1-61499-341-6
• Descrizione fisica: 1 online resource (154 p.)
• Collana: Studies on the Semantic Web, , 1868-1158 ; ; Volume 007
• Disciplina: 006.3/31
• Soggetti: Knowledge acquisition (Expert systems); Problem solving - Data processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Title Page; List of figures; List of Tables; Contents; Introduction; State of the Art; The Knowledge Acquisition Bottleneck; From Mining to Modelling: The Knowledge Level; Ontologies and Problem Solving Methods in the Knowledge Acquisition Modelling Paradigm; Knowledge Acquisition by Knowledge Engineers; Knowledge Acquisition by Subject Matter Experts; Process Knowledge and Subject Matter Experts; The Process Knowledge Lifecycle; Conclusions; Work Objectives; Goals and Open Research Problems; Contributions to the State of the Art; Work Assumptions, Hypotheses, and Restrictions; Acquisition of Process Knowledge by SMEsIntroduction; Knowledge Acquisition and Formulation by SMEs in the Halo Project; Knowledge Types in Scientific Disciplines; Domain Analysis; A Comprehensive Set of Knowledge Types in Scientific Disciplines; The Process Metamodel; Process Entities in the Process Metamodel; Problem Solving Methods for the Acquisition of Process Knowledge; A PSM Modelling Framework for Processes; A Method to Build a PSM Library of Process Knowledge; A PSM Library for the Acquisition of Process Knowledge; Enabling SMEs to Formulate Process Knowledge; The DarkMatter Process EditorRelated Work; Representing and Reasoning with SME-authored Process Knowledge; A Formalism for Representing and Reasoning with Process Knowledge; F-logic as Process Representation and Reasoning Language; The Process Frame; ; Code Generation for Process Knowledge; Synthesis of precedence rules for data flow management; Code Synthesis for Iterative Actions; Soundness and Completeness of Process Models; Optimization of the Synthesized Process Code; Reasoning with Process Models; Analysis of Process Executions by SMEs; Towards Knowledge Provenance in Process Analysis; Problem Solving Methods for the Analysis of Process ExecutionsA Knowledgeoriented Provenance Environment; An Algorithm for Process Analysis Using PSMs; Evaluation; Evaluation of the DarkMatter Process Component for Acquisition of Process Knowledge by SMEs; Evaluation Syllabus; Distribution of the Formulated Processes across the Evaluation Syllabus; Utilization of the PSM Library and Process Metamodel; Usage Experience of the SMEs with the Process Editor; Performance Evaluation of the Process Component; Evaluation of KOPE for the Analysis of Process Executions by SMEs; Evaluation Settings; Evaluation MetricsEvaluation Results; Evaluation Conclusions; Conclusions and Future Research; Conclusions; Future Research Problems; REFERENCES; Appendix. Sample F-logic Code for a Process Model
• Sommario/riassunto: The development of knowledge-based systems is usually approached through the combined skills of knowledge engineers (KEs) and subject matter experts (SMEs). One of the most critical steps in this activity aims at transferring knowledge from SMEs to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this is a costly and error prone task. Alleviating the knowledge acquisition bottleneck requires enabling SMEs with the means to produce the desired knowledge representations without the help of KEs. This is especially difficult in the case of compl