Mejorando las técnicas de verificación de wrappers web mediante técnicas bioinspiradas y de clasificación

Muchas Aplicaciones Empresariales necesitan de los wrappers para poder tratar con información proveniente de la web profunda. Los wrappers son sistemas automáticos que permiten navegar, extraer, estructurar y verificar información relevante proveniente de la web. Uno de sus elementos, el extractor de información, está formado por una serie de reglas de extracción que suelen estar basadas en etiquetas HTML. Por tanto, si las fuentes cambian, el wrapper, en algunos casos, puede devolver información no deseada por la empresa y provocar, en el mejor de los casos, retrasos en sus tomas de decisión. Diversos sistemas de verificación de wrappers se han desarrollado con el objetivo de detectar automáticamente cuándo un wrapper está extrayendo datos incorrectos. Estos sistemas presentan una serie de carencias cuyo origen radica en asumir que los datos a verificar siguen una serie de características estadísticas preestablecidas. En esta disertación se analizan estos sistemas, se diseña un marco de trabajo para desarrollar verificadores y se aborda el problema de la verificación desde dos puntos de vista distintos. Inicialmente lo ubicaremos dentro de la rama de la optimización computacional y lo resolveremos aplicando metaheúristicas bioinspiradas como es la basada en colonias en hormigas, en concreto aplicaremos el algoritmo BWAS; con posterioridad, lo formularemos y resolveremos como si de un problema de clasificación no supervisada se tratara. Fruto de este segundo enfoque surge MAVE, un verificador multinivel cuya base principal son los clasificadores de una única clase.Many Enterprise Applications require wrappers to deal with information from the deep web. Wrappers are automated systems that allow you to navigate, extract, reveal structures and verify information from the web. One of its elements, the information extractor, is formed by extraction rules series that are usually based on HTML tags. Therefore, if you change sources, the wrapper, in some cases, may return unwanted information by the company and cause, at the best, delays in their decision-making process. Some wrappers verification systems have been developed to automatically detect when a wrapper is taking out incorrect data. These systems have a number of shortcomings whose origin lies in assuming that the data to verify follow a series of pre statistics. This dissertation analyzes these systems, a framework is designed to develop verifiers and the verification problem is approached from two different points of view. Initially, we place it within the branch of computational optimization and solve it applying bio-inspired metaheuristic as it is found in ant colonies, specifically we will apply the BWAS algorithm. Subsequently we will formulate and solve as if it were a unsupervised classification problem. The result of this second approach is MAVE, a multilevel verifier whose main base are the unique class classifiers

FOLMO: first order logic in Moodle

La Lógica, dirigida a estudiantes universitarios de Ingeniería, aporta al alumno una visión razonada del aprendizaje basada en la formalización del conocimiento y en la automatización de distintas formas del razonamiento humano [6]. Con el objetivo de potenciar su aprendizaje nace First Order Logic in Moodle (FOLMO), un software de fácil integración con Moodle que permite el trabajo autónomo del alumno mediante la realización de ejercicios propuestos por el profesor.Peer Reviewe

FOLMO: First Order Logic in Moodle

La Lógica, dirigida a estudiantes universitarios de Ingeniería, aporta al alumno una visión razonada del aprendizaje basada en la formalización del conocimiento y en la automatización de distintas formas del razonamiento humano [6]. Con el objetivo de potenciar su aprendizaje nace First Order Logic in Moodle (FOLMO), un software de fácil integración con Moodle que permite el trabajo autónomo del alumno mediante la realización de ejercicios propuestos por el profesor

Integrating Deep-Web Information Sources

Deep-web information sources are difficult to integrate into automated business processes if they only provide a search form. A wrapping agent is a piece of software that allows a developer to query such information sources without worrying about the details of interacting with such forms. Our goal is to help soft ware engineers construct wrapping agents that interpret queries written in high-level structured languages. We think that this shall definitely help reduce integration costs because this shall relieve developers from the burden of transforming their queries into low-level interactions in an ad-hoc manner. In this paper, we report on our reference framework, delve into the related work, and highlight current research challenges. This is intended to help guide future research efforts in this area.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-

Analysis of the best-worst ant system and its variants on the tsp

Abstract. In this contribution, we will study the influence of the three components of the Best-Worst Ant System (BWAS) algorithm. As the importance of each of them as the fact whether all of them are necessary will be analyzed. Besides, we will introduce a new algorithm called Best-Worst Ant Colony System by combining the basis of the Ant Colony System with the special components of the BWAS. The performance of different variants of these algorithms will be tested when solving different instances of the QAP.

Genetic Hybrid Optimization of a Real Bike Sharing System

In recent years there has been a growing interest in resource sharing systems as one of the possible ways to support sustainability. The use of resource pools, where people can drop a resource to be used by others in a local context, is highly dependent on the distribution of those resources on a map or graph. The optimization of these systems is an NP-Hard problem given its combinatorial nature and the inherent computational load required to simulate the use of a system. Furthermore, it is difficult to determine system overhead or unused resources without building the real system and test it in real conditions. Nevertheless, algorithms based on a candidate solution allow measuring hypothetical situations without the inconvenience of a physical implementation. In particular, this work focuses on obtaining the past usage of bike loan network infrastructures to optimize the station’s capacity distribution. Bike sharing systems are a good model for resource sharing systems since they contain common characteristics, such as capacity, distance, and temporary restrictions, which are present in most geographically distributed resources systems. To achieve this target, we propose a new approach based on evolutionary algorithms whose evaluation function will consider the cost of non-used bike places as well as the additional kilometers users would have to travel in the new distribution. To estimate its value, we will consider the geographical proximity and the trend in the areas to infer the behavior of users. This approach, which improves user satisfaction considering the past usage of the former infrastructure, as far as we know, has not been applied to this type of problem and can be generalized to other resource sharing problems with usage data.FEDER 2014–2020, Junta de Andalucía and Universidad de Huelva, project UHU-1266216 and the Ministerio Español de Economía y Competitividad, projects TIN2017-85727-C4-2-P (UGR-DeepBio) and PID2020-115570GB-C22 (DemocratAI::UGR)

FOLMO: first order logic in Moodle

La Lógica, dirigida a estudiantes universitarios de Ingeniería, aporta al alumno una visión razonada del aprendizaje basada en la formalización del conocimiento y en la automatización de distintas formas del razonamiento humano [6]. Con el objetivo de potenciar su aprendizaje nace First Order Logic in Moodle (FOLMO), un software de fácil integración con Moodle que permite el trabajo autónomo del alumno mediante la realización de ejercicios propuestos por el profesor.Peer Reviewe