Gutierrez C.,University of Chile |
Hurtado C.A.,Adolfo Ibanez University |
Perez J.,University of Computer Science of Chile
Journal of Computer and System Sciences | Year: 2011
The Semantic Web is based on the idea of a common and minimal language to enable large quantities of existing data to be analyzed and processed. This triggers the need to develop the database foundations of this basic language, which is the Resource Description Framework (RDF). This paper addresses this challenge by: 1) developing an abstract model and query language suitable to formalize and prove properties about the RDF data and query language; 2) studying the RDF data model, minimal and maximal representations, as well as normal forms; 3) studying systematically the complexity of entailment in the model, and proving complexity bounds for the main problems; 4) studying the notions of query answering and containment arising in the RDF data model; and 5) proving complexity bounds for query answering and query containment. © 2010 Elsevier Inc. All rights reserved.
Alvarez C.,University of Los Andes, Chile |
Salavati S.,Linnaeus University |
Nussbaum M.,University of Computer Science of Chile |
Milrad M.,Linnaeus University
Computers and Education | Year: 2013
Education systems worldwide must strive to support the teaching of a set of New Media Literacies (NMLs). These literacies respond to the need for educating human capital within participatory cultures in a highly technologized world. In this paper, we present Collboard, a constructivist problem solving activity for fostering the development of specific NMLs in classrooms: collective intelligence, distributed cognition and transmedia navigation. Collboard encompasses successive individual and collaborative work phases that prompt active student participation and engagement. It integrates digitally augmented appliances, namely, digital pens as a means to support individual work, and interactive whiteboards as a collaborative knowledge construction space. We report on the conceptual design of Collboard, its different technological and software components, as well as our findings from experiences we conducted in a Swedish school with 12 students from a 7th grade maths class. Findings from the experience provide an indication that Collboard can be well integrated in classroom teaching, and that it can foster the development of collective intelligence, distributed cognition and transmedia navigation in different knowledge domains.2013 Elsevier Ltd. All rights reserved.
Aldunate R.,Catholic University of Temuco |
Nussbaum M.,University of Computer Science of Chile
Computers in Human Behavior | Year: 2013
Technology adoption is usually modeled as a process with dynamic transitions between costs and benefits. Nevertheless, school teachers do not generally make effective use of technology in their teaching. This article describes a study designed to exhibit the interplay between two variables: the type of technology, in terms of its complexity of use, and the type of teacher, in terms of attitude towards innovation. The results from this study include: (a) elaboration of a characteristic teacher technology adoption process, based on an existing learning curve for new technology proposed for software development; and (b) presentation of exit points during the technology adoption process. This paper concludes that teachers who are early technology adopters and commit a significant portion of their time to incorporating educational technology into their teaching are more likely to adopt new technology, regardless of its complexity. However, teachers who are not early technology adopters and commit a small portion of their time to integrating educational technology are less likely to adopt new technology and are prone to abandoning the adoption at identified points in the process. © 2012 Elsevier Ltd. All rights reserved.
Montero E.,University of Nice Sophia Antipolis |
Montero E.,University of Computer Science of Chile |
Riff M.-C.,University of Computer Science of Chile
Information Sciences | Year: 2011
The issue of controlling values of various parameters of an evolutionary algorithm is one of the most important and interesting areas of research in evolutionary computation. In this paper we propose two new parameter control strategies for evolutionary algorithms based on the ideas of reinforcement learning. These strategies provide efficient and low-cost adaptive techniques for parameter control and they preserve the original design of the evolutionary algorithm, as they can be included without changing either the structure of the algorithm nor its operators design. © 2010 Elsevier Inc. All rights reserved.
Garrido P.,University of Computer Science of Chile |
Riff M.C.,University of Computer Science of Chile
Journal of Heuristics | Year: 2010
In this paper we propose and evaluate an evolutionary-based hyper-heuristic approach, called EH-DVRP, for solving hard instances of the dynamic vehicle routing problem. A hyper-heuristic is a high-level algorithm, which generates or chooses a set of low-level heuristics in a common framework, to solve the problem at hand. In our collaborative framework, we have included three different types of low-level heuristics: constructive, perturbative, and noise heuristics. Basically, the hyper-heuristic manages and evolves a sophisticated sequence of combinations of these low-level heuristics, which are sequentially applied in order to construct and improve partial solutions, i.e., partial routes. In presenting some design considerations, we have taken into account the allowance of a proper cooperation and communication among low-level heuristics, and as a result, find the most promising sequence to tackle partial states of the (dynamic) problem. Our approach has been evaluated using the Kilby's benchmarks, which comprise a large number of instances with different topologies and degrees of dynamism, and we have compared it with some well-known methods proposed in the literature. The experimental results have shown that, due to the dynamic nature of the hyper-heuristic, our proposed approach is able to adapt to dynamic scenarios more naturally than low-level heuristics. Furthermore, the hyper-heuristic can obtain high-quality solutions when compared with other (meta) heuristic-based methods. Therefore, the findings of this contribution justify the employment of hyper-heuristic techniques in such changing environments, and we believe that further contributions could be successfully proposed in related dynamic problems. © 2010 Springer Science+Business Media, LLC.