Defeasible Argumentation over Relational Databases

CRISTHIAN A. D. DEAGUSTINI; SANTIAGO E. FULLADOZA DALIBÓN; SEBASTIÁN GOTTIFREDI; MARCELO A. FALAPPA; CARLOS I. CHESÑEVAR; GUILLERMO R. SIMARI

Argument and Computation

IOS Press

Lugar: New York; Año: 2017 vol. 8 p. 35 - 59

1946-2166

Defeasibleargumentation has been applied successfully in several real-world domains inwhich it is necessary to handle incomplete and contradictory information. Inrecent years, there have been interesting attempts to carry out argumentationprocesses supported by massive repositories developing argumentative reasoningapplications. This article presents eDBI- DeLP, which extends the originalDBI-DeLP framework by providing two novel aspects which refine the interactionbetween DeLP programs and relational databases. First, we expand the expressivenessof dbi-delp programs by providing ways of controlling how the information indatabases is recovered; this is done by introducing filters that enable animproved fine-grained control on the argumentation processes which become usefulin applications, providing the semantics and the implementation of suchfilters. Second, we introduce an argument comparison criterion which can beadjusted at the level of literals to model particular features such ascredibility and topic expertise, among others. These new tools can beparticularly useful in environments such as medical diagnosis expert systems,decision support systems, or recommender systems based on argumentation, where datasetsare often provided in the form of relational databases.