Àgora. La experiencia de la Escuela de personas adultas. La verneda-Sant Martí: del aprendizaje de las tecnologías al contexto de aprendizaje tecnológico

La Comunidad de Aprendizaje Escuela de personas adultas La Verneda-Sant Martí, lleva más de 10 años trabajando las tecnologías de la información y la comunicación desde una perspectiva transversal y global. A través del trabajo que venimos realizando día a día, hemos visto como las TIC han pasado de ser una necesidad formativa a convertirse en un contexto de aprendizaje cotidiano entre las personas que participan de nuestro proyecto. Desde que en 1999 decidimos transformar nuestras actividades para integrarnos plenamente en la sociedad de la información hemos cambiado metodologías, prioridades y formas de trabajar. Mostrar cuáles han sido esas transformaciones y qué resultados son los que se han alcanzado es el principal reto del artículo.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

WikiSAC: sistema col·laboratiu per a l’ atenció ciutadana en administracions municipals

L’objectiu dels Serveis Intel·ligents d’Atenció Ciutadana (SAC) és donar resposta a les necessitats d'informació dels ciutadans sobre els serveis i les actuacions del municipi i, per extensió, del conjunt del serveis d'interès ciutadà. Des que l’ iSAC s’ha posat en funcionament, periòdicament s’analitzen les consultes que es fan en el sistema i el grau de satisfacció que la ciutadania té d’aquest servei. Tot i que en general les valoracions són satisfactòries s’ha observat que actualment aquest sistema té un buit, hi ha un ampli ventall de respostes que, de moment, l’iSAC no és capaç de resoldre, i possiblement el 010, el call center del servei d’atenció ciutadana, tampoc. Algunes de les cerques realitzades marxen molt de l’àmbit municipal i és l’experiència de la mateixa ciutadania la que pot oferir un millor resultat. És per aquest motiu que ha sorgit la necessitat de crear wikiSAC. Eina que te com a principals objectius que: poder crear, modificar i eliminar el contingut d’una pàgina de forma interactiva de manera fàcil i ràpida a través d’un navegador web; controlar els continguts ofensius i malintencionats; conservar un historial de canvis; incentivar la participació ciutadana i aconseguir que aquest sigui un lloc on els ciutadans preguntin, suggereixin i opinin sobre temes relacionats amb el seu municipi i aconseguir que els ciutadans es sentin més integrats amb el funcionament de l’administració, col∙laborant en les tasques d’informació i atenció ciutadana

Common Craft

Common craft make short videos which explain in simple terms some common concepts and technologies used in learning and teaching. These are available through The Common Craft Store, which offers versions of videos that are: Downloadable files Presentation-quality Licensed for workplace use You can find the free, online versions of the videos on The Common Craft Show. Topics include phishing, RSS, wikis, Twitter, social networking, social bookmarking, web search strategies, social media, podcasting, sharing photos online and many more.

Impacto de la apertura en la conectividad e integración de Colombia en la red mundial de comercio

La liberalización colombiana es analizada, con frecuencia, con los coeficientes de apertura, este documento, en cambio, presenta un análisis complementario a través de algoritmos usados en la teoría de redes para caracterizar sistemas complejos. Esta nueva aproximación devela estructuras de la red mundial de comercio antes y después de la apertura, así como cambios en la posición colombiana.

Göra illa för att hjälpa eller hjälpa till att göra illa? : Arbetslösas reservationslöner, jobbchanser och återanställningsinkomster

Hurting to help or helping to hurt? The reservation wages of unemployed, job chances and reemployment incomes in Sweden Economic incentives and their impact on the job search behaviour of the unemployed have been a central focus in the academic and political debate in Sweden. A key concept has been the reservation wages of the unemployed, the lowest income at which an unemployed person would be willing to accept a job offer. Unemployment benefit systems have been argued to raise and maintain reservation wages at high levels that lower job chances. This has been supported by a large number of international studies. From this perspective lower reservation wages would function as protection against long term unemployment and the scarring effects associated with it. High reservation wages might however, based on the same behavioural assumptions, have a human capital preserving effect. The possibility to hold out for the right job should reduce human capital losses compared to accepting the first available job offer. In this article we use Swedish longitudinal micro data combining interview and register data in order to investigate three central aspects reservation wages in a Swedish context: factors influencing the setting of reservation wages, the effect of reservation wage on job chances and the impact of reservation wages on reemployment incomes. Our findings show that benefit level and pre-unemployment position in the wage structure are central factors for setting the reservation wage. The effects of reservation wages were however not the expected. No effects were found on job chances, while a strong positive effect was found on reemployment income. This together indicates that high reservation wages have a human capital preserving effect in Sweden.

Foraging by the omnivorous crab Pachygrapsus transversus affects the structure of assemblages on sub-tropical rocky shores

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Trait-mediated effects on flowers: Artificial spiders deceive pollinators and decrease plant fitness

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fraseologismos zoônimos: elaboração de base de dados Português-Francês

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Atividades investigativas em grupos online: possibilidades para a educação matemática a distância

Pós-graduação em Educação Matemática - IGCE

Un approccio per la concettualizzazione di insiemi di documenti

Introduzione a tecniche di web semantico e realizzazione di un approccio in grado di ricreare un ambiente familiare di un qualsiasi motore di ricerca con funzionalità semantico-lessicali e possibilità di estrazione, in base ai risultati di ricerca, dei concetti e termini chiave che costituiranno i relativi gruppi di raccolta per i vari documenti con argomenti in comune.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

Multipedia: Enriching DBpedia with Multimedia Information

Enriching knowledge bases with multimedia information makes it possible to complement textual descriptions with visual and audio information. Such complementary information can help users to understand the meaning of assertions, and in general improve the user experience with the knowledge base. In this paper we address the problem of how to enrich ontology instances with candidate images retrieved from existing Web search engines. DBpedia has evolved into a major hub in the Linked Data cloud, interconnecting millions of entities organized under a consistent ontology. Our approach taps into the Wikipedia corpus to gather context information for DBpedia instances and takes advantage of image tagging information when this is available to calculate semantic relatedness between instances and candidate images. We performed experiments with focus on the particularly challenging problem of highly ambiguous names. Both methods presented in this work outperformed the baseline. Our best method leveraged context words from Wikipedia, tags from Flickr and type information from DBpedia to achieve an average precision of 80%.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results: We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions: CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

A formalism and method for representing and reasoning with process models authored by subject matter experts

Enabling Subject Matter Experts (SMEs) to formulate knowledge without the intervention of Knowledge Engineers (KEs) requires providing SMEs with methods and tools that abstract the underlying knowledge representation and allow them to focus on modeling activities. Bridging the gap between SME-authored models and their representation is challenging, especially in the case of complex knowledge types like processes, where aspects like frame management, data, and control flow need to be addressed. In this paper, we describe how SME-authored process models can be provided with an operational semantics and grounded in a knowledge representation language like F-logic in order to support process-related reasoning. The main results of this work include a formalism for process representation and a mechanism for automatically translating process diagrams into executable code following such formalism. From all the process models authored by SMEs during evaluation 82% were well-formed, all of which executed correctly. Additionally, the two optimizations applied to the code generation mechanism produced a performance improvement at reasoning time of 25% and 30% with respect to the base case, respectively.