By Naeem Khalid Janjua
This booklet stories at the improvement and validation of a universal defeasible common sense programming framework for conducting argumentative reasoning in Semantic internet purposes (GF@SWA). The proposed technique is exclusive in offering an answer for representing incomplete and/or contradictory info coming from diverse assets, and reasoning with it. GF@SWA is ready to characterize this kind of details, practice argumentation-driven hybrid reasoning to unravel conflicts, and generate graphical representations of the built-in info, hence aiding determination makers in selection making strategies. GF@SWA represents the 1st argumentative reasoning engine for accomplishing automatic reasoning within the Semantic net context and is predicted to have an important influence on destiny company purposes. The booklet offers the readers with an in depth and transparent exposition of alternative argumentation-based reasoning recommendations, and in their value and use in Semantic internet functions. It addresses either teachers and execs, and may be of fundamental curiosity to researchers, scholars and practitioners within the sector of Web-based clever selection help platforms and their software in numerous domains.
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Extra info for A Defeasible Logic Programming-Based Framework to Support Argumentation in Semantic Web Applications
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12. Chapters 5, 6 and 7 are all elaborations on the conceptual framework presented in Chap. 4. 10 Conclusion This chapter introduced the Semantic Web and discussed the ontology languages layer and logic layer in detail. The limitations of current development technologies on the logic layer which results in certain challenges for Semantic Web applications were outlined. The importance of defeasible reasoning and argumentation techniques as suitable candidates to address the challenges faced by Semantic Web applications in the area of BI was detailed.
Exploitation of GF@SWA in different Semantic Web applications as follows: (a) Design and develop a Web-based Intelligent DSS for representation and reasoning over incomplete and/or contradictory information to assist the decision maker in decision making process. (b) Design and develop a Web-based Intelligent DSS for enterprise knowledge integration. (c) Design and develop a Web-based Intelligent DSS for process map discovery from business policies. 24 1 Introduction 5. Evaluate and validate the proposed framework and Semantic Web applications with the help of case studies and implementation.