By Naeem Khalid Janjua
This e-book studies at the improvement and validation of a common defeasible common sense programming framework for undertaking argumentative reasoning in Semantic net purposes (GF@SWA). The proposed method is exclusive in delivering an answer for representing incomplete and/or contradictory details coming from assorted resources, and reasoning with it. GF@SWA is ready to characterize this sort of details, practice argumentation-driven hybrid reasoning to solve conflicts, and generate graphical representations of the built-in info, therefore supporting choice makers in selection making tactics. GF@SWA represents the 1st argumentative reasoning engine for conducting automatic reasoning within the Semantic internet context and is anticipated to have an important influence on destiny company purposes. The ebook presents the readers with a close and transparent exposition of alternative argumentation-based reasoning recommendations, and in their significance and use in Semantic internet purposes. It addresses either teachers and pros, and should be of fundamental curiosity to researchers, scholars and practitioners within the region of Web-based clever choice help structures and their program in quite a few domains.
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Extra info for A Defeasible Logic Programming-Based Framework to Support Argumentation in Semantic Web Applications
He distinguished six parts in argument structure and presented these in a diagrammatic representation, as depicted in Fig. 1. The elements are: 1. Claims: Every argument makes assertions based on data. The assertion of an argument is the claim of the argument. 2. Grounds: Data and hard facts, plus the reasoning behind the claim to establish the foundation of the claim. 3. Warrants: Evidence and reasoning to justify the move from grounds to claim. Warrants are not self-validating. 4. Backing: The backing (or support) for an argument gives additional support to the warrant by answering different questions.
But, as discussed in the first scenario, the current Semantic Web lacks the capability to represent, reason and integrate incomplete and/or contradictory information. This, in turn, renders an enterprise incapable of knowledge integration; that is, the integration of knowledge about a subject that could be incomplete, contradictory and distributed among different Web-based DSS within an enterprise or in other enterprises. This can be elucidated with the help of an example where the higher level management of an enterprise asks for recommendations from different departments about selecting a relocation service provider.
2. e. warrant, this might mean questioning the knowledge used in the current context or questioning the inference rules. 3. If inconsistencies can be detected in the opponent’s background knowledge, challenge the backing. 1 summarizes the different extensions made to Toulmin’s model of argument representation. Each of these extensions is made keeping in view the purpose to be fulfilled in a specific domain, as illustrated in the table. 2 Argumentation Schemes Proposed by Walton and Reed Argumentation schemes provide a way to perform reasoning over a set of premises and a conclusion.