1,721,028 research outputs found
Aplicación de machine learning a la detección de fake news
Full text linkLos medios digitales han logrado un notable crecimiento en el último tiempo impulsado por la masificación de internet y los dispositivos móviles, proporcionando un canal de información más para la producción, difusión y consumo de noticias por parte de las personas y las empresas. Sin embargo, como contrapartida, también se ha convertido en un medio propicio para la propagación de información falsa, popularmente conocidas por el término fake news, con un impacto significativo en la toma de decisiones de los usuarios.
En este contexto, la Inteligencia Artificial, y particularmente las técnicas de minería de texto basadas en aprendizaje automático han ganado gran popularidad gracias a los resultados alentadores que han obtenido en la lucha contra esta problemática. A pesar de los avances logrados, varios estudios coinciden en que la tarea de detección automática de fake news continúa siendo un tema desafiante para la comunidad científica debido a que presentan características complejas que dificultan la aplicación efectiva de muchas soluciones existentes.
El objetivo general de este trabajo es explorar las bases teóricas de las técnicas utilizadas en minería de texto y su aplicación al problema de detección de fake news a fin de contribuir al desarrollo de nuevas soluciones en este campo. Para lograr esto, esta tesis presenta un estudio de desempeño de un algoritmo base para el problema de detección de fake news, evaluando diversos ensayos que combinan diferentes configuraciones de hiperparametros y distintas técnicas de selección de características. Además, también se aplican diferentes técnicas de procesamiento de lenguaje natural sobre un dataset de noticias, analizando la relevancia de cada una. Finalmente, se elabora un cuadro comparativo que permite visualizar el impacto de las distintas configuraciones, midiendo accuracy, precision, recall y f1-measure.Especialista en Inteligencia de Datos orientada a Big DataUniversidad Nacional de La PlataFacultad de Informátic
A Probabilistic Logic of Cyber Deception
Full text linkMalicious attackers often scan nodes in a network in order to identify vulnerabilities that they may exploit as they traverse the network. In this paper, we propose that the system generates a mix of true and false answers in response to scan requests. If the attacker believes that all scan results are true, then he will be on a wrong path. If he believes some scan results are faked, he would have to expend time and effort in order to separate fact from fiction. We propose a probabilistic logic of deception and show that various computations are NP-hard. We model the attacker’s state and show the effects of faked scan results. We then show how the defender can generate fake scan results in different states that minimize the damage the attacker can produce. We develop a Naive-PLD algorithm and a Fast-PLD heuristic algorithm for the defender to use and show experimentally that the latter performs well in a fraction of the run time of the former. We ran detailed experiments to assess the performance of these algorithms and further show that by running Fast-PLD off-line and storing the results, we can very efficiently answer run-time scan requests
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Ontological CP−Nets
No full textRepresenting and reasoning about preferences is a key issue in many real-world scenarios in which personalized access to information is required. Many approaches have been proposed and studied in the literature that allow a system to work with qualitative or quantitative preferences; among the qualitative models, one of the most prominent are CP-nets. Their clear graphical structure unifies an easy representation of user preferences with good computational properties when computing the best outcome. In this paper, we show how to reason with CP-nets when the attributes modeling the knowledge domain are structured via an underlying domain ontology. We show how the computation of all undominated feasible outcomes of an ontological CP-net can be reduced to the solution of a constraint satisfaction problem, and study the computational complexity of the basic reasoning problems in ontological CP-nets
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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