Universidad Nacional de La Plata (UNLP) Intellectual Creativity Diffusion Service (SeDiCI) was formed mainly to publicise the knowledge acquired at the different academic areas of our university, having the goal of restoring to the community the efforts expended on public…

Nowadays, data intensive applications are in constant demand and there is need of computing environments with better intelligent capabilities than those present in today's Database Management Systems (DBMS). To build such systems we need formalisms that can perform complicate inferences,…

Defeasible Logic Programming (DeLP) is a knowledge representation formalism that combines results from Logic Programming and Defeasible Argumentation to provide reasoning based on contradictory and potentially incomplete information. DeLP allows information representation by using weak rules and provides an argumentation…

There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construct a fish-disease diagnostic model to effectively deal with…

As many authors have stated, the importance of organizational learning is fundamental in order to gain competitive advantage and survive in a turbulent environment. Many learning models have been studied in recent years. They have been used to analyze practices…

This paper addresses the problem of contour line extraction from scanned topographic maps in poor condition. A novel method is developed, using knowledge of cartography and graphics to extract contours by removing other layers which overlay the contours, and reconstructing…

Artificial Intelligence deals with the challenge of modeling commonsense reasoning. In the last fifteen years argument-based systems have came forward to meet this challenge as knowledge representation and reasoning tools able to model incomplete and conflicting information. We believe that…

In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the…

Knowledge acquisition for systems based on knowledge can be called knowledge engineering, according to Feigenbaum (1980) who used the term to describe the reduction of a wide context of knowledge for a set of facts and rules. The term Knowledge…

Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component…