Un caso de estudio de pronóstico de los resultados electorales: más allá de la predicción basada en business intelligence

In the field of data analysis, it is common not to distinguish clearly between prediction and forecast. Although the results of both processes may tend to converge, the mechanisms used in each case tend to be completely different. Prediction has to do with statistical extrapolation and estimation and forecasting can consider expert judgments on the subject. A methodology is proposed to carry out this latter task, with a mechanism that uses both historical and current data with the judgement of an expert. The methodology is applied to the case study of the Spanish general elections of April 2019.En el campo del análisis de datos, es común no distinguir claramente entre predicción y pronóstico. Aunque los resultados de ambos procesos pueden tender a converger, los mecanismos utilizados en cada caso tienden a ser completamente diferentes. La predicción tiene que ver con la extrapolación estadística y la estimación y el pronóstico puede considerar el juicio de expertos sobre el tema. Se propone una metodología para llevar a cabo esta última tarea, con un mecanismo que utiliza tanto datos históricos como actuales con el juicio de un experto para afinar el resultado. La metodología se aplica al estudio de caso de las elecciones generales españolas de abril de 2019.Facultad de Informátic

Un caso de estudio de pronóstico de los resultados electorales: más allá de la predicción basada en business intelligence

In the field of data analysis, it is common not to distinguish clearly between prediction and forecast. Although the results of both processes may tend to converge, the mechanisms used in each case tend to be completely different. Prediction has to do with statistical extrapolation and estimation and forecasting can consider expert judgments on the subject. A methodology is proposed to carry out this latter task, with a mechanism that uses both historical and current data with the judgement of an expert. The methodology is applied to the case study of the Spanish general elections of April 2019.En el campo del análisis de datos, es común no distinguir claramente entre predicción y pronóstico. Aunque los resultados de ambos procesos pueden tender a converger, los mecanismos utilizados en cada caso tienden a ser completamente diferentes. La predicción tiene que ver con la extrapolación estadística y la estimación y el pronóstico puede considerar el juicio de expertos sobre el tema. Se propone una metodología para llevar a cabo esta última tarea, con un mecanismo que utiliza tanto datos históricos como actuales con el juicio de un experto para afinar el resultado. La metodología se aplica al estudio de caso de las elecciones generales españolas de abril de 2019.Facultad de Informátic

Búsqueda eficaz de información en la web

En este trabajo se describe someramente lo que es un Sistema de Recuperación de Información, para posteriormente poder profundizar en algunos aspectos específicos. Se presentan las herramientas de búsqueda Web más usadas actualmente, haciendo especial hincapié en los buscadores y en los metabuscadores, con el fin de proporcionar ciertos “trucos” para ayudar a mejorar nuestro acceso y búsqueda en los contenidos de la Web (por ejemplo explicando el uso de algunos operadores de búsqueda, cómo funcionan los algoritmos de ranking, como mejorar la posición de una página Web en los buscadores o cuáles son las peculiaridades de las arquitecturas computacionales de algunos motores de búsqueda). Finalmente, se propone el desarrollo y pruebas de mecanismos más “inteligentes” de acceso, búsqueda, gestión y recuperación de información y conocimiento contenidos en la Web. Para ello se muestra el uso de técnicas avanzadas de Inteligencia Artificial, en particular aquellas más cercanas a la manipulación del lenguaje natural y al comportamiento humano.XV Escuela Internacional de Informática, realizada durante el XVII Congreso Argentino de Ciencia de la Computación (CACIC 2011).Red de Universidades con Carreras en Informática (RedUNCI

Búsqueda eficaz de información en la web

En este trabajo se describe someramente lo que es un Sistema de Recuperación de Información, para posteriormente poder profundizar en algunos aspectos específicos. Se presentan las herramientas de búsqueda Web más usadas actualmente, haciendo especial hincapié en los buscadores y en los metabuscadores, con el fin de proporcionar ciertos “trucos” para ayudar a mejorar nuestro acceso y búsqueda en los contenidos de la Web (por ejemplo explicando el uso de algunos operadores de búsqueda, cómo funcionan los algoritmos de ranking, como mejorar la posición de una página Web en los buscadores o cuáles son las peculiaridades de las arquitecturas computacionales de algunos motores de búsqueda). Finalmente, se propone el desarrollo y pruebas de mecanismos más “inteligentes” de acceso, búsqueda, gestión y recuperación de información y conocimiento contenidos en la Web. Para ello se muestra el uso de técnicas avanzadas de Inteligencia Artificial, en particular aquellas más cercanas a la manipulación del lenguaje natural y al comportamiento humano.XV Escuela Internacional de Informática, realizada durante el XVII Congreso Argentino de Ciencia de la Computación (CACIC 2011).Red de Universidades con Carreras en Informática (RedUNCI

Forest fire prediction using fuzzy prototypical knowledge discovery

An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following daysI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Data Analytics for the Cryptocurrencies Behavior

The cryptocurrencies are a new paradigm of transferring money be-tween users. Their anonymous and non-centralized is a subject of debate around the globe that paired with the massive spikes and declines in value that are in-herit to an unregistered asset. These facts make difficult for the common daily use of the cryptocurrencies as an exchange currency as instead they are being used as a new way to invest. What we propose in this article is a system for the better understanding of the cryptocurrencies economical behavior against the global market. For that we are using Data Analytics techniques to build a pre-dictor that uses as inputs said external financial variable. These forecasts would help determine if a coin is safe to trade with, if those forecasts can be precise by only using this external data. The results obtained indicates us that there is a certain degree of influence of the global market to the cryptocurrencies, but that is it not enough to correctly predict the fluctuations in price of the coins and that they care more about others factors and that they have their own bubbles, like the crypto collapse in late 2017.Instituto de Investigación en Informátic

Un caso de estudio de pronóstico de los resultados electorales: más allá de la predicción basada en business intelligence

In the field of data analysis, it is common not to distinguish clearly between prediction and forecast. Although the results of both processes may tend to converge, the mechanisms used in each case tend to be completely different. Prediction has to do with statistical extrapolation and estimation and forecasting can consider expert judgments on the subject. A methodology is proposed to carry out this latter task, with a mechanism that uses both historical and current data with the judgement of an expert. The methodology is applied to the case study of the Spanish general elections of April 2019.En el campo del análisis de datos, es común no distinguir claramente entre predicción y pronóstico. Aunque los resultados de ambos procesos pueden tender a converger, los mecanismos utilizados en cada caso tienden a ser completamente diferentes. La predicción tiene que ver con la extrapolación estadística y la estimación y el pronóstico puede considerar el juicio de expertos sobre el tema. Se propone una metodología para llevar a cabo esta última tarea, con un mecanismo que utiliza tanto datos históricos como actuales con el juicio de un experto para afinar el resultado. La metodología se aplica al estudio de caso de las elecciones generales españolas de abril de 2019.Facultad de Informátic

Forest fire prediction using fuzzy prototypical knowledge discovery

An application of Zadeh’s prototype theory in the Knowledge Acquisition process, is presented here, and as a practical example, to define a method for predicting the evolution of the forest fire occurrence-danger rate in INCEND-IA: A KBS for prediction and decision support in fighting against forest fires. This method then allows us to interpret any real cyclical situation using a previously discovered paradigm and define the current period. The FPKD (Fuzzy Prototypical Knowledge Discovery) is presented as a mechanism with the aim of generating Prototypes of Data (A new set of data sufficiently representative to be able to summarize or assimilate the behavior of any of the remaining data); but the concept of prototype is a fuzzy concept and Zadeh’s Theory provides an appropriate framework for its application. Data Mining techniques have been used (decision trees, time series, clustering...). Thus, it is possible to calculate the grade of compatibility of a real situation with the prototypes and define the current period using these affinity values, with the objective of predicting the evolution of the following daysI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Satellite Orbit Prediction Using Big Data and Soft Computing Techniques to Avoid Space Collisions

The number of satellites and debris in space is dangerously increasing through the years. For that reason, it is mandatory to design techniques to approach the position of a given object at a given time. In this paper, we present a system to do so based on a database of satellite positions according to their coordinates (x,y,z) for one month. We have paid special emphasis on the preliminary stage of data arrangement, since if we do not have consistent data, the results we will obtain will be useless, so the first stage of this work is a full study of the information gathered locating the missing gaps of data and covering them with a prediction. With that information, we are able to calculate an orbit error which will estimate the position of a satellite in time, even when the information is not accurate, by means of prediction of the satellite’s position. The comparison of two satellites over 26 days will serve to highlight the importance of the accuracy in the data, provoking in some cases an estimated error of 4% if the data are not well measured.Instituto de Investigación en Informátic

User-Oriented Summaries Using a PSO Based Scoring Optimization Method

Automatic text summarization tools have a great impact on many fields, such as medicine, law, and scientific research in general. As information overload increases, automatic summaries allow handling the growing volume of documents, usually by assigning weights to the extracted phrases based on their significance in the expected summary. Obtaining the main contents of any given document in less time than it would take to do that manually is still an issue of interest. In this article, a new method is presented that allows automatically generating extractive summaries from documents by adequately weighting sentence scoring features using Particle Swarm Optimization. The key feature of the proposed method is the identification of those features that are closest to the criterion used by the individual when summarizing. The proposed method combines a binary representation and a continuous one, using an original variation of the technique developed by the authors of this paper. Our paper shows that using user labeled information in the training set helps to find better metrics and weights. The empirical results yield an improved accuracy compared to previous methods used in this field.Instituto de Investigación en Informátic