Download A Defeasible Logic Programming-Based Framework to Support by Naeem Khalid Janjua PDF

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By Naeem Khalid Janjua

This ebook studies at the improvement and validation of a established defeasible good judgment programming framework for engaging in argumentative reasoning in Semantic internet functions (GF@SWA). The proposed technique is exclusive in delivering an answer for representing incomplete and/or contradictory info coming from various assets, and reasoning with it. GF@SWA is ready to signify this kind of info, practice argumentation-driven hybrid reasoning to unravel conflicts, and generate graphical representations of the built-in info, hence helping determination makers in choice making strategies. GF@SWA represents the 1st argumentative reasoning engine for undertaking automatic reasoning within the Semantic net context and is predicted to have an important impression on destiny company purposes. The booklet presents the readers with a close and transparent exposition of other argumentation-based reasoning innovations, and in their value and use in Semantic internet purposes. It addresses either teachers and pros, and may be of fundamental curiosity to researchers, scholars and practitioners within the region of Web-based clever selection aid platforms and their software in a variety of domains.

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ACM, NY, USA, pp 48–57 Horrocks I, Parsia B, Patel-Schneider P, Hendler J (2005) Semantic web architecture: stack or two towers? In: Fages F, Soliman S (eds) Principles and practice of semantic web reasoning. Lecture notes in computer science, vol 3703. Springer, Berlin, pp 37–41 Kontopoulos E, Bassiliades N, Antoniou G (2008) Deploying defeasible logic rule bases for the semantic web. Data Knowl Eng 66(1):116–146 Lee T, Hendler J, Lassila O et al (2001) The semantic web. Sci Am 284(5):34–43 Lee TB (2003) The semantic web and challenges.

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Inductive arguments sometimes use statistical techniques to establish the strength (or confidence) of the supported claim. The reasoning based on inductive arguments is known as inductive reasoning. • In a presumptive argument, the conclusions are said to be plausible given the premises. Plausibility is different from probability. While probability is determined by reasoning from statistical evidence, plausibility states that the conclusion holds by default provided no adequate evidence supports the contrary view.

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