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Acquisition and understanding of process knowledge using problem solving methods

Author: José Manuel Gómez-Pérez
Publisher: [Amsterdam] : IOS Press : AKA, [2010] ©2010
Series: Studies on the Semantic Web, v. 007.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Gómez-Pérez, José Manuel.
Acquisition and understanding of process knowledge using problem solving methods
(DLC) 2011514750
(OCoLC)669738864
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: José Manuel Gómez-Pérez
ISBN: 9781614993414 1614993416 1306284767 9781306284769
OCLC Number: 868068573
Description: 1 online resource (x, 144 pages) : illustrations.
Contents: 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.
Series Title: Studies on the Semantic Web, v. 007.
Responsibility: José Manuel Gómez-Pérez.

Abstract:

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 application domains uncovers that process knowledge is one of the most freqent knowledge types, whose complexity requires specific means to enable SMEs to represent processes in a computational form. Additionally, such complexity and the increasigly large amount of data that process executions generate in knowledge-intensive domains, like Biology or Astronomy, requires analytical means with high abstraction capabilities to support SMEs in the analysis of such processes. This book presents methods and tools that enable SMEs to acquire process knowledge from the domains, formally represent such knowledge, reason about it, and understand process executions by analyzing their provenance. We describe the utilization of Problem Solving Methods as the main knowledge artifacts for process acquisition and analysis in two innovative ways. First, as formalizations of the reasoning strategies needed for processes and, second, as high-level, domain-independent, and reusable abstractions of process knowledge to provide SMEs with interpretati-ons of process executions--P.4 of cover.

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