A new multidimensional model with text dimensions: definition and implementation

We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic way, without user’s intervention, so all the classical operations in the multidimensional model can been defined for this textual dimension. While most of the models dealing with texts that can be found in the literature are not implemented, in this proposal, the multidimensional model and the OLAP system have been implemented in a software tool, so it can be tested on real data. A case study with medical data is included in this work.Junta de Andalucia P07-TIC02786 P10-TIC6109 P11-TIC746

Systems of possibilistic regressions: a case study in ecological inference

This work introduces how possibilistic regression can be used in the case of non symmetrical triangular membership functions, building a system of regressions, so that suitable restrictions for each particular problem can be incorporated. We apply this methodology to the problem of ecological inference, in particular to the estimation of the electoral transition matrix. An experimentation with several examples shows the benefits of the new approach

Fuzzy cardinality based evaluation of quanti®ed sentences

Quantified statements are used in the resolution of a great variety of problems. Several methods have been proposed to evaluate statements of types I and II. The objective of this paper is to study these methods, by comparing and generalizing them. In order to do so, we propose a set of properties that must be fulfilled by any method of evaluation of quantified statements, we discuss some existing methods from this point of view and we describe a general approach for the evaluation of quantified statements based on the fuzzy cardinality and fuzzy relative cardinality of fuzzy sets. In addition, we discuss some concrete methods derived from the mentioned approach. These new methods fulfill all the properties proposed and, in some cases, they provide an interpretation or generalization of existing methods

A first approach to the multipurpose relational database server

In this paper, an architecture and an implementation of a multipurpose relational database server are proposed. This architecture enables classical queries to be executed, deductions to be made, and data mining operations to be performed on fuzzy or classical data. The proposal of this integration is to combine several ways of querying different types of data. In order to achieve this, a combination of existing metaknowledge bases and new data catalog elements is presented. We also introduce a language for handling all these data coherently and uniformly on the basis of classical SQL sentences

Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions

Over the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we present a recommendation system capable of using different input sources (data and knowledge-based) and producing a complex structured output. We have used an evolutionary approach to combine several unitary items within a flexible structure and have built an initial set of complex configurable items. Then, a content-based approach refines (in terms of preferences) these candidates to offer a final recommendation.We conclude with the application of this approach to the healthy diet recommendation problem, addressing its strengths in this domain.Over the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we present a recommendation system capable of using different input sources (data and knowledge-based) and producing a complex structured output. We have used an evolutionary approach to combine several unitary items within a flexible structure and have built an initial set of complex configurable items. Then, a content-based approach refines (in terms of preferences) these candidates to offer a final recommendation.We conclude with the application of this approach to the healthy diet recommendation problem, addressing its strengths in this domainEuropean Union (Stance4Health) under Grant 816303Ministerio de Ciencia e Innovación under Grant PID2021-123960OB-I00MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia estatal de Investigacion)/10.13039/501100011033ERDF (European Regional Development Fund)A way of making Europe. And in part under Grant TED2021-129402B-C21 funded by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia estatal de Investigacion)/10.13039/501100011033European Union NextGenerationEU/PRTR (Plan de Recuperación, Transformación y Resiliencia)‘Program of Information and Communication technologies’’ at the University of Granad

Aplicación de las TICs en el Ámbito de la Construcción

La industria de la construcción posee una serie de características propias que la hacen muy diferente de otros sectores industriales; entre ellas destaca la gran cantidad de agentes que intervienen en el proceso constructivo y la cantidad de documentación que se genera y necesita desde la fase de diseño hasta la terminación del proyecto. La complejidad de los proyectos conlleva que cada uno de ellos sea diferente, único y singular, lo que hace más difícil la toma de decisiones y genera claramente la necesidad de disponer de sistemas que aporten la información necesaria a los decisores en cada momento. En este sentido, las TICs ofrecen una herramienta inmejorable.Hoy en día no basta con utilizar técnicas efectivas de almacenamiento y recuperación de datos, sino que también es necesario desarrollar técnicas que nos permitan explorar la “mina de oro” que suponen los datos operacionales recolectados en relación con la información que pueden aportar sobre el funcionamiento del negocio que los genera. En este trabajo, se presenta la arquitectura de un sistema de información integrado de gestión de la información para el sector de la construcción que contempla tanto la faceta operacional, para dar soporte al funcionamiento diario de los agentes involucrados en el proceso, como una faceta analítica que incorpora un valor añadido a la hora de afrontar la toma de decisiones estratégicas durante el desarrollo del proceso

A fuzzy-based medical system for pattern mining in a distributed environment: Application to diagnostic and co-morbidity

In this paper we have addressed the extraction of hidden knowledge from medical records using data mining techniques such as association rules in conjunction with fuzzy logic in a distributed environment. A significant challenge in this domain is that although there are a lot of studies devoted to analysing health data, very few focus on the understanding and interpretability of the data and the hidden patterns present within the data. A major challenge in this area is that many health data analysis studies have focussed on classification, prediction or knowledge extraction and end users find little interpretability or understanding of the results. This is due to the use of black-box algorithms or because the nature of the data is not represented correctly. This is why it is necessary to focus the analysis not only on knowledge extraction but also on the transformation and processing of the data to improve the modelling of the nature of the data. Techniques such as association rule mining and fuzzy logic help to improve the interpretability of the data and treat it with the inherent uncertainty of real-world data. To this end, we propose a system that automatically: a) pre-processes the database by transforming and adapting the data for the data mining process and enriching the data to generate more interesting patterns, b) performs the fuzzification of the medical database to represent and analyse real-world medical data with its inherent uncertainty, c) discovers interrelations and patterns amongst different features (diagnostic, hospital discharge, etc.), and d) visualizes the obtained results efficiently to facilitate the analysis and improve the interpretability of the information extracted. Our proposed system yields a significant increase in the compression and interpretability of medical data for end-users, allowing them to analyse the data correctly and make the right decisions. We present one practical case using two health-related datasets to demonstrate the feasibility of our proposal for real data.Junta de Andalucia P18-RT-1765Ministry of Universities through the E

Segmenting colour images on the basis of a fuzzy hierarchical approach

In this paper we deal with two problems related to imprecision in colour image segmentation processes: to decide whether a set of pixels verify the property "to be homogeneously coloured", and to represent the set of possible segmentations of an image at different precision levels. In order to solve the first problem we introduce a measure of distance between colours in the CIE L*a*b* space, that allows us to measure the degree of homogeneity of two pixels p and q on the basis of the maximum distance between the colours of consecutive pairs of pixels in any path linking p and q . Since homogeneity is a matter of degree, we define a (fuzzy) segmentation of an image as a set of fuzzy regions, each of them being a fuzzy subset of pixels, that we obtain by using a region growing technique. The membership degree of each pixel to each region is calculated on the basis of our homogeneity measure. The second problem is solved by introducing a fuzzy similarity relation between the fuzzy regions in this initial segmentation. The different α-cuts of the similarity relation define the set of precision levels, from which a nested hierarchy of fuzzy segmentations is finally obtained

A Flexible Approach to the Multidimensional Model: The Fuzzy Datacube

As a result of the use of OLAP technology in new fields of knowledge and the merge of data from different sources, it has become necessary for models to support this technology. In this paper, we propose a new multidimensional model that can manage imprecision both in dimensions and facts. Consequently, the multidimensional structure is able to model data imprecision resulting from the integration of data from different sources or even information from experts, which it does by means of fuzzy logic

Construcción de un sistema de información y de ayuda a la decisión mediante lógica difusa para el cultivo del olivar en Andalucía

In Southern Spain, olive (Olea europaea L.) growing is an important part of the economy, especially in the provinces of Jaén, Córdoba and Granada. This work proposes the first stages of an Information and Decision-Support System (IDSS) for providing different types of users (farmers, agricultural engineers, public services, etc.) with information on olive growing and the environment, and also assisting in decision-making. The main purposes of the project reported in this paper are to process uncertain or imprecise data, such as those concerning the environment or crops, and combine user data with other scientific-experimental data. The possibility of storing agricultural and ecological information in fuzzy relational databases, vital to the development of an IDSS is described. The information will be processed using knowledge extraction tools (fuzzy data-mining) that will allow rules on expert knowledge for assessing suitability of land to be developed and making thematic maps with the aid of Geographic Information Systems. Flexible querying will allow the users to collect information interactively from databases, while user information is constantly added. Flexible querying of databases, land suitability and thematic maps may be used to help in decisionmaking.El cultivo del olivo (Olea europaea L.) tiene una enorme importancia económica en la zona sur de España y concretamente en las provincias de Jaén, Córdoba y Granada. En este trabajo se propone la construcción de un sistema de información y ayuda a la toma de decisión (IDSS) que permita en el futuro a distintos tipos de usuarios (agricultores, agrónomos, administraciones públicas, etc.) obtener y manejar información sobre el cultivo de olivar y el soporte ambiental del mismo, así como ayudar en la toma de decisiones. Los principales objetivos desarrollados en este trabajo son el tratamiento de datos inciertos e imprecisos, como es el caso de la información ambiental y sobre cultivos, y la fusión de datos sobre cultivo y otros de carácter científico-experimental. Se describe la posibilidad de almacenar la información de carácter agronómico y ecológico en bases de datos relacionales, que es vital para el desarrollo de un IDSS. La información será procesada a través de herramientas de extracción de conocimiento (minería de datos difusa) y permitirá sobre la base del conocimiento experto el desarrollo de reglas para la clasificación de aptitud del terreno y para la obtención de mapas temáticos con la ayuda de Sistemas de Información Geográfica. La consulta flexible permitirá a los distintos usuarios la consulta interactiva de toda la información almacenada en las bases de datos, así como una implementación constante de las mismas. La consulta flexible de bases de datos, la idoneidad de los terrenos y los mapas temáticos pueden ser de gran utilidad en la toma de decisiones.This work is part of the research projects 1FD97-0244-CO3-2 (financed with FEDER funds) and CGL2004-02282BTE (Spanish Ministry of Education and Science)