Argumentation is a form of reasoning where a claim is accepted or rejected according to the analysis of the arguments for and against it; furthermore, it provides a reasoning mechanism able to handle contradictory, incomplete and uncertain information in real-world situations. We combine Bipolar Argumentation Frameworks (an extension of Dung’s work) with an Algebra of Argumentation Labels modeling two independent types of interaction between arguments, representing meta-information associated with arguments, and introducing an acceptability notion that will give more information for (...) arguments acceptability. (shrink)

In this paper a hybrid model of argument from analogy is presented that combines argumentation schemes and story schemes. One premise of the argumentation scheme for argument from analogy in the model claims that one case is similar to another. Story schemes are abstract representations of stories (narratives, explanations) based on common knowledge about how sequences of actions and events we are familiar with can normally be expected to unfold. Story schemes are used (a) to model similarity between two cases, (...) and (2) as the basis of evidence to support the similarity premise of an argument from analogy. Four examples of argument from analogy are used to test the theory. (shrink)

In this paper, it is shown (1) that there are two schemes for argument from analogy that seem to be competitors but are not, (2) how one of them is based on a distinctive type of similarity premise, (3) how to analyze the notion of similarity using story schemes illustrated by some cases, (4) how arguments from precedent are based on arguments from analogy, and in many instances arguments from classification, and (5) that when similarity is defined by means of (...) episode schemes, we can get a clearer idea of how it integrates with the use of argument from classification and argument from precedent in case-based reasoning by using a dialogue structure. (shrink)

Semantic similarity and relatedness between concepts have been extensively studied in different areas ranging from psychology to computational linguistics. In this paper we address the problem of determining the similarity between concepts defined in a knowledge source such as an ontology. The focus is measuring similarity between concepts from the same ontology. We propose a concept similarity algorithm based on geometric models for representing concepts and relationships, which can be applied to different types of ontologies. The key idea is the (...) concept weighting scheme which allows for quantifying the degree of abstractness of concepts. The evaluation settings involving two ontologies validate and highlight the advantages and disadvantages of the proposed approach. Using the proposed measure, which closely resembles the human judgment of similarity, we can reliably recreate predefined concept clusters, and generate more informative concept paths. (shrink)

Argumentation represents a way of reasoning over a knowledge base containing possibly incomplete and/or inconsistent information, to obtain useful conclusions. As a reasoning mechanism, the way an argumentation reasoning engine reaches these conclusions resembles the cognitive process that humans follow to analyze their beliefs; thus, unlike other computationally reasoning systems, argumentation offers an intellectually friendly alternative to other defeasible reasoning systems. LogicProgrammingisacomputationalparadigmthathasproducedcompu- tationallyattractivesystemswithremarkablesuccessinmanyapplications. Merging ideas from both areas, Defeasible Logic Programming offers a computational reasoning system that uses an argumentation engine (...) to obtain answers from a knowledge base represented using a logic programming language extended with defeasible rules. This combination of ideas brings about a computationally effective system together with a human-like reasoning model facilitating its use in applications. (shrink)