A Defeasible Logic Programming-Based Framework to Support Argumentation in Semantic Web Applications [electronic resource] / by Naeem Khalid Janjua.

By: Janjua, Naeem Khalid [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextLanguage: English Series: Springer Theses, Recognizing Outstanding Ph.D. Research: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XVII, 301 p. 110 illus., 4 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319039497Subject(s): Engineering | Data mining | Artificial intelligence | Operations research | Engineering | Computational Intelligence | Data Mining and Knowledge Discovery | Operation Research/Decision Theory | e-Commerce/e-business | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q342Online resources: Click here to access online
Contents:
Problem Definition -- Solution Overview -- Argumentation-enabled Web-based Intelligent Decision Support System -- Enterprise Knowledge Integration through Argumentation enabled Intelligent Decision Support Systems -- Process Map Discovery from Business Policies: A Knowledge Representation approach with Argumentative Reasoning -- Validation and Evaluation of GF@SWA -- Recapitulation and Future Work.
In: Springer eBooksSummary: This book reports on the development and validation of a generic defeasible logic programming framework for carrying out argumentative reasoning in Semantic Web applications (GF@SWA). The proposed methodology is unique in providing a solution for representing incomplete and/or contradictory information coming from different sources, and reasoning with it. GF@SWA is able to represent this type of information, perform argumentation-driven hybrid reasoning to resolve conflicts, and generate graphical representations of the integrated information, thus assisting decision makers in decision making processes. GF@SWA represents the first argumentative reasoning engine for carrying out automated reasoning in the Semantic Web context and is expected to have a significant impact on future business applications. The book provides the readers  with a detailed and clear exposition of different argumentation-based reasoning techniques, and of their importance and use in Semantic Web applications. It addresses both academics and professionals, and will be of primary interest to researchers, students and practitioners in the area of Web-based intelligent decision support systems and their application in various domains.
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Problem Definition -- Solution Overview -- Argumentation-enabled Web-based Intelligent Decision Support System -- Enterprise Knowledge Integration through Argumentation enabled Intelligent Decision Support Systems -- Process Map Discovery from Business Policies: A Knowledge Representation approach with Argumentative Reasoning -- Validation and Evaluation of GF@SWA -- Recapitulation and Future Work.

This book reports on the development and validation of a generic defeasible logic programming framework for carrying out argumentative reasoning in Semantic Web applications (GF@SWA). The proposed methodology is unique in providing a solution for representing incomplete and/or contradictory information coming from different sources, and reasoning with it. GF@SWA is able to represent this type of information, perform argumentation-driven hybrid reasoning to resolve conflicts, and generate graphical representations of the integrated information, thus assisting decision makers in decision making processes. GF@SWA represents the first argumentative reasoning engine for carrying out automated reasoning in the Semantic Web context and is expected to have a significant impact on future business applications. The book provides the readers  with a detailed and clear exposition of different argumentation-based reasoning techniques, and of their importance and use in Semantic Web applications. It addresses both academics and professionals, and will be of primary interest to researchers, students and practitioners in the area of Web-based intelligent decision support systems and their application in various domains.

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